default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDYann LeCun
Yann André LeCun
Person information
- affiliation: New York University, Courant Institute of Mathematical Sciences, USA
- affiliation: Facebook
- award (2018): Turing Award
SPARQL queries 
🛈 Please note that only 54% of the items listed on this page have a DOI stored with their dblp record. Therefore, DOI-based queries can only provide partial results.
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2026
[i192]Matthieu Destrade, Oumayma Bounou, Quentin Le Lidec, Jean Ponce, Yann LeCun:
Value-guided action planning with JEPA world models. CoRR abs/2601.00844 (2026)- [i191]Quentin Garrido, Tushar Nagarajan, Basile Terver, Nicolas Ballas, Yann LeCun, Michael Rabbat:
Learning Latent Action World Models In The Wild. CoRR abs/2601.05230 (2026) - [i190]Shengbang Tong, Boyang Zheng, Ziteng Wang, Bingda Tang, Nanye Ma, Ellis Brown, Jihan Yang, Rob Fergus, Yann LeCun, Saining Xie:
Scaling Text-to-Image Diffusion Transformers with Representation Autoencoders. CoRR abs/2601.16208 (2026) - [i189]Michael Psenka, Michael Rabbat, Aditi Krishnapriyan, Yann LeCun, Amir Bar:
Parallel Stochastic Gradient-Based Planning for World Models. CoRR abs/2602.00475 (2026) - [i188]Yilun Kuang, Yash Dagade, Tim G. J. Rudner, Randall Balestriero, Yann LeCun:
Rectified LpJEPA: Joint-Embedding Predictive Architectures with Sparse and Maximum-Entropy Representations. CoRR abs/2602.01456 (2026) - [i187]Basile Terver, Randall Balestriero, Megi Dervishi, David Fan, Quentin Garrido, Tushar Nagarajan, Koustuv Sinha, Wancong Zhang, Mike Rabbat, Yann LeCun, Amir Bar:
A Lightweight Library for Energy-Based Joint-Embedding Predictive Architectures. CoRR abs/2602.03604 (2026) - [i186]Lucas Maes, Quentin Le Lidec, Dan Haramati, Nassim Massaudi, Damien Scieur, Yann LeCun, Randall Balestriero:
stable-worldmodel-v1: Reproducible World Modeling Research and Evaluation. CoRR abs/2602.08968 (2026) - [i185]Georgios Ioannides, Adrian Kieback, Judah Goldfeder, Linsey Pang, Aman Chadha, Aaron Elkins, Yann LeCun, Ravid Shwartz-Ziv:
Soft Clustering Anchors for Self-Supervised Speech Representation Learning in Joint Embedding Prediction Architectures. CoRR abs/2602.09040 (2026) - [i184]Heejeong Nam, Quentin Le Lidec, Lucas Maes, Yann LeCun, Randall Balestriero:
Causal-JEPA: Learning World Models through Object-Level Latent Interventions. CoRR abs/2602.11389 (2026) - [i183]Yilun Kuang, Yash Dagade, Deep Chakraborty, Erik G. Learned-Miller, Randall Balestriero, Tim G. J. Rudner, Yann LeCun:
Radial-VCReg: More Informative Representation Learning Through Radial Gaussianization. CoRR abs/2602.14272 (2026) - [i182]Hai Huang, Yann LeCun, Randall Balestriero:
Semantic Tube Prediction: Beating LLM Data Efficiency with JEPA. CoRR abs/2602.22617 (2026) - [i181]Judah Goldfeder, Philippe Martin Wyder, Yann LeCun, Ravid Shwartz Ziv:
AI Must Embrace Specialization via Superhuman Adaptable Intelligence. CoRR abs/2602.23643 (2026) - [i180]Shengbang Tong, David Fan, John Nguyen, Ellis Brown, Gaoyue Zhou, Shengyi Qian, Boyang Zheng, Théophane Vallaeys, Junlin Han, Rob Fergus, Naila Murray, Marjan Ghazvininejad, Mike Lewis, Nicolas Ballas, Amir Bar, Michael Rabbat, Jakob Verbeek, Luke Zettlemoyer, Koustuv Sinha, Yann LeCun, Saining Xie:
Beyond Language Modeling: An Exploration of Multimodal Pretraining. CoRR abs/2603.03276 (2026) - [i179]Deming Chen, Jason Cong, Azalia Mirhoseini, Christos Kozyrakis, Subhasish Mitra, Jinjun Xiong, Cliff Young, Anima Anandkumar, Michael L. Littman, Aron Kirschen, Sophia Shao, Serge Leef, Naresh R. Shanbhag, Dejan S. Milojicic, Michael Schulte, Gert Cauwenberghs, Jerry M. Chow, Tri Dao, Kailash Gopalakrishnan, Richard Ho, Hoshik Kim, Kunle Olukotun, David Z. Pan, Mark Ren, Dan Roth, Aarti Singh, Yizhou Sun, Yusu Wang, Yann LeCun, Ruchir Puri:
AI+HW 2035: Shaping the Next Decade. CoRR abs/2603.05225 (2026) - [i178]Shangwen Sun, Alfredo Canziani, Yann LeCun, Jiachen Zhu:
The Spike, the Sparse and the Sink: Anatomy of Massive Activations and Attention Sinks. CoRR abs/2603.05498 (2026) - [i177]Ying Wang, Oumayma Bounou, Gaoyue Zhou, Randall Balestriero, Tim G. J. Rudner, Yann LeCun, Mengye Ren:
Temporal Straightening for Latent Planning. CoRR abs/2603.12231 (2026) - [i176]Helen Qu, Rudy Morel, Michael McCabe, Alberto Bietti, François Lanusse, Shirley Ho, Yann LeCun:
Representation Learning for Spatiotemporal Physical Systems. CoRR abs/2603.13227 (2026) - [i175]Lorenzo Mur-Labadia, Matthew J. Muckley, Amir Bar, Mido Assran, Koustuv Sinha, Mike Rabbat, Yann LeCun, Nicolas Ballas, Adrien Bardes:
V-JEPA 2.1: Unlocking Dense Features in Video Self-Supervised Learning. CoRR abs/2603.14482 (2026) - [i174]Emmanuel Dupoux, Yann LeCun, Jitendra Malik:
Why AI systems don't learn and what to do about it: Lessons on autonomous learning from cognitive science. CoRR abs/2603.15381 (2026) - [i173]Lucas Maes, Quentin Le Lidec, Damien Scieur, Yann LeCun, Randall Balestriero:
LeWorldModel: Stable End-to-End Joint-Embedding Predictive Architecture from Pixels. CoRR abs/2603.19312 (2026) - 2025
- [c202]William Rudman, Michal Golovanevsky, Amir Bar, Vedant Palit, Yann LeCun, Carsten Eickhoff, Ritambhara Singh:
Forgotten Polygons: Multimodal Large Language Models are Shape-Blind. ACL (Findings) 2025: 11983-11998 - [c201]Deep Chakraborty, Yann LeCun, Tim G. J. Rudner, Erik G. Learned-Miller:
Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization. AISTATS 2025: 433-441 - [c200]Raktim Gautam Goswami, Prashanth Krishnamurthy, Yann LeCun, Farshad Khorrami:
RoboPEPP: Vision-Based Robot Pose and Joint Angle Estimation through Embedding Predictive Pre-Training. CVPR 2025: 6930-6939 - [c199]Jiachen Zhu, Xinlei Chen, Kaiming He, Yann LeCun, Zhuang Liu:
Transformers without Normalization. CVPR 2025: 14901-14911 - [c198]Amir Bar, Gaoyue Zhou, Danny Tran, Trevor Darrell, Yann LeCun:
Navigation World Models. CVPR 2025: 15791-15801 - [c197]Tal Zeevi, Ravid Shwartz-Ziv, Yann LeCun, Lawrence H. Staib, John A. Onofrey
:
Rate-In: Information-Driven Adaptive Dropout Rates for Improved Inference-Time Uncertainty Estimation. CVPR 2025: 20757-20766 - [c196]Megi Dervishi, Alexandre Allauzen, Gabriel Synnaeve, Yann LeCun:
Training compute-optimal transformer encoder models. EMNLP 2025: 35614-35629 - [c195]Nicklas Hansen, Jyothir S. V, Vlad Sobal, Yann LeCun, Xiaolong Wang, Hao Su:
Hierarchical World Models as Visual Whole-Body Humanoid Controllers. ICLR 2025 - [c194]Md Rifat Arefin, Gopeshh Subbaraj, Nicolas Gontier, Yann LeCun, Irina Rish, Ravid Shwartz-Ziv, Christopher Pal:
Seq-VCR: Preventing Collapse in Intermediate Transformer Representations for Enhanced Reasoning. ICLR 2025 - [c193]Vlad Sobal, Mark Ibrahim, Randall Balestriero, Vivien Cabannes, Diane Bouchacourt, Pietro Astolfi, Kyunghyun Cho, Yann LeCun:
X-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs. ICLR 2025 - [c192]Alex N. Wang, Christopher Hoang, Yuwen Xiong, Yann LeCun, Mengye Ren:
PooDLe🐩: Pooled and dense self-supervised learning from naturalistic videos. ICLR 2025 - [c191]Colin White, Samuel Dooley, Manley Roberts, Arka Pal, Benjamin Feuer, Siddhartha Jain, Ravid Shwartz-Ziv, Neel Jain, Khalid Saifullah, Sreemanti Dey, Shubh-Agrawal, Sandeep Singh Sandha, Siddartha V. Naidu, Chinmay Hegde, Yann LeCun, Tom Goldstein, Willie Neiswanger, Micah Goldblum:
LiveBench: A Challenging, Contamination-Limited LLM Benchmark. ICLR 2025 - [c190]Zeyu Yun, Juexiao Zhang, Yann LeCun, Yubei Chen:
URLOST: Unsupervised Representation Learning without Stationarity or Topology. ICLR 2025 - [c189]Oscar Skean, Md Rifat Arefin, Dan Zhao, Niket Patel, Jalal Naghiyev, Yann LeCun, Ravid Shwartz-Ziv:
Layer by Layer: Uncovering Hidden Representations in Language Models. ICML 2025 - [c188]Gaoyue Zhou, Hengkai Pan, Yann LeCun, Lerrel Pinto:
DINO-WM: World Models on Pre-trained Visual Features enable Zero-shot Planning. ICML 2025 - [d2]Yann LeCun, Han Xiao, Alex Krizhevsky:
A Collection of Foundational Image Classification Datasets (MNIST, Fashion-MNIST, CIFAR-10, CIFAR-100). IEEE DataPort, 2025
- [i172]Oscar Skean, Md Rifat Arefin, Dan Zhao, Niket Patel, Jalal Naghiyev, Yann LeCun, Ravid Shwartz-Ziv:
Layer by Layer: Uncovering Hidden Representations in Language Models. CoRR abs/2502.02013 (2025) - [i171]Quentin Garrido, Nicolas Ballas, Mahmoud Assran, Adrien Bardes, Laurent Najman, Michael Rabbat, Emmanuel Dupoux, Yann LeCun:
Intuitive physics understanding emerges from self-supervised pretraining on natural videos. CoRR abs/2502.11831 (2025) - [i170]Vlad Sobal, Wancong Zhang, Kynghyun Cho, Randall Balestriero, Tim G. J. Rudner, Yann LeCun:
Learning from Reward-Free Offline Data: A Case for Planning with Latent Dynamics Models. CoRR abs/2502.14819 (2025) - [i169]William Rudman, Michal Golovanesky, Amir Bar, Vedant Palit, Yann LeCun, Carsten Eickhoff, Ritambhara Singh:
Forgotten Polygons: Multimodal Large Language Models are Shape-Blind. CoRR abs/2502.15969 (2025) - [i168]Jiachen Zhu, Xinlei Chen, Kaiming He, Yann LeCun, Zhuang Liu:
Transformers without Normalization. CoRR abs/2503.10622 (2025) - [i167]David Fan, Shengbang Tong, Jiachen Zhu, Koustuv Sinha, Zhuang Liu, Xinlei Chen, Michael Rabbat, Nicolas Ballas, Yann LeCun, Amir Bar, Saining Xie:
Scaling Language-Free Visual Representation Learning. CoRR abs/2504.01017 (2025) - [i166]Chen Shani, Dan Jurafsky, Yann LeCun, Ravid Shwartz-Ziv:
From Tokens to Thoughts: How LLMs and Humans Trade Compression for Meaning. CoRR abs/2505.17117 (2025) - [i165]Raktim Gautam Goswami, Prashanth Krishnamurthy, Yann LeCun, Farshad Khorrami:
OSVI-WM: One-Shot Visual Imitation for Unseen Tasks using World-Model-Guided Trajectory Generation. CoRR abs/2505.20425 (2025) - [i164]Mido Assran, Adrien Bardes, David Fan, Quentin Garrido, Russell Howes, Mojtaba Komeili, Matthew J. Muckley, Ammar Rizvi, Claire Roberts, Koustuv Sinha, Artem Zholus, Sergio Arnaud, Abha Gejji, Ada Martin, Francois Robert Hogan, Daniel Dugas, Piotr Bojanowski, Vasil Khalidov, Patrick Labatut, Francisco Massa, Marc Szafraniec, Kapil Krishnakumar, Yong Li, Xiaodong Ma, Sarath Chandar, Franziska Meier, Yann LeCun, Michael Rabbat, Nicolas Ballas:
V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning. CoRR abs/2506.09985 (2025) - [i163]Yutong Bai, Danny Tran, Amir Bar, Yann LeCun, Trevor Darrell, Jitendra Malik:
Whole-Body Conditioned Egocentric Video Prediction. CoRR abs/2506.21552 (2025) - [i162]Federico Baldassarre, Marc Szafraniec, Basile Terver, Vasil Khalidov, Francisco Massa, Yann LeCun, Patrick Labatut, Maximilian Seitzer, Piotr Bojanowski:
Back to the Features: DINO as a Foundation for Video World Models. CoRR abs/2507.19468 (2025) - [i161]Hai Huang, Yann LeCun, Randall Balestriero:
LLM-JEPA: Large Language Models Meet Joint Embedding Predictive Architectures. CoRR abs/2509.14252 (2025) - [i160]Randall Balestriero, Nicolas Ballas, Mike Rabbat, Yann LeCun:
Gaussian Embeddings: How JEPAs Secretly Learn Your Data Density. CoRR abs/2510.05949 (2025) - [i159]Enrique Queipo-de-Llano, Alvaro Arroyo, Federico Barbero, Xiaowen Dong, Michael M. Bronstein, Yann LeCun, Ravid Shwartz-Ziv:
Attention Sinks and Compression Valleys in LLMs are Two Sides of the Same Coin. CoRR abs/2510.06477 (2025) - [i158]Shusheng Yang, Jihan Yang, Pinzhi Huang, Ellis Brown, Zihao Yang, Yue Yu, Shengbang Tong, Zihan Zheng, Yifan Xu, Muhan Wang, Daohan Lu, Rob Fergus, Yann LeCun, Li Fei-Fei, Saining Xie:
Cambrian-S: Towards Spatial Supersensing in Video. CoRR abs/2511.04670 (2025) - [i157]Randall Balestriero, Yann LeCun:
LeJEPA: Provable and Scalable Self-Supervised Learning Without the Heuristics. CoRR abs/2511.08544 (2025) - [i156]James Ni, Zekai Wang, Wei Lin, Amir Bar, Yann LeCun, Trevor Darrell, Jitendra Malik, Roei Herzig:
From Generated Human Videos to Physically Plausible Robot Trajectories. CoRR abs/2512.05094 (2025) - [i155]Georgios Ioannides, Christos Constantinou, Aman Chadha, Aaron Elkins, Linsey Pang, Ravid Shwartz-Ziv, Yann LeCun:
JEPA as a Neural Tokenizer: Learning Robust Speech Representations with Density Adaptive Attention. CoRR abs/2512.07168 (2025) - [i154]Arjun Parthasarathy, Nimit Kalra, Rohun Agrawal, Yann LeCun, Oumayma Bounou, Pavel Izmailov, Micah Goldblum:
Closing the Train-Test Gap in World Models for Gradient-Based Planning. CoRR abs/2512.09929 (2025) - [i153]Delong Chen, Mustafa Shukor, Théo Moutakanni, Willy Chung, Jade Yu, Tejaswi Kasarla, Allen Bolourchi, Yann LeCun, Pascale Fung:
VL-JEPA: Joint Embedding Predictive Architecture for Vision-language. CoRR abs/2512.10942 (2025) - [i152]Raktim Gautam Goswami, Amir Bar, David Fan, Tsung-Yen Yang, Gaoyue Zhou, Prashanth Krishnamurthy, Michael Rabbat, Farshad Khorrami, Yann LeCun:
World Models Can Leverage Human Videos for Dexterous Manipulation. CoRR abs/2512.13644 (2025) - [i151]Mahi Luthra, Jiayi Shen, Maxime Poli, Angelo Ortiz, Yosuke Higuchi, Youssef Benchekroun, Martin Gleize, Charles-Éric Saint-James, Dongyan Lin, Phillip Rust, Angel Villar, Surya Parimi, Vanessa Stark, Rashel Moritz, Juan Pino, Yann LeCun, Emmanuel Dupoux:
SpidR-Adapt: A Universal Speech Representation Model for Few-Shot Adaptation. CoRR abs/2512.21204 (2025) - [i150]Basile Terver, Tsung-Yen Yang, Jean Ponce, Adrien Bardes, Yann LeCun:
What Drives Success in Physical Planning with Joint-Embedding Predictive World Models? CoRR abs/2512.24497 (2025) - 2024
- [j50]Wancong Zhang, Anthony GX-Chen, Vlad Sobal, Yann LeCun, Nicolas Carion:
Light-weight Probing of Unsupervised Representations for Reinforcement Learning. RLJ 4: 1924-1949 (2024) - [j49]Ravid Shwartz-Ziv, Yann LeCun:
To Compress or Not to Compress - Self-Supervised Learning and Information Theory: A Review. Entropy 26(3): 252 (2024) - [j48]Li Liu, Timothy M. Hospedales, Yann LeCun, Mingsheng Long, Jiebo Luo, Wanli Ouyang, Matti Pietikäinen, Tinne Tuytelaars:
Editorial: Learning With Fewer Labels in Computer Vision. IEEE Trans. Pattern Anal. Mach. Intell. 46(3): 1319-1326 (2024) - [j47]Adrien Bardes, Quentin Garrido, Jean Ponce, Xinlei Chen, Michael Rabbat, Yann LeCun, Mido Assran, Nicolas Ballas:
Revisiting Feature Prediction for Learning Visual Representations from Video. Trans. Mach. Learn. Res. 2024 (2024) - [j46]Shoaib Ahmed Siddiqui, David Krueger, Yann LeCun, Stéphane Deny:
Blockwise Self-Supervised Learning at Scale. Trans. Mach. Learn. Res. 2024 (2024) - [c187]Shengbang Tong, Xili Dai, Yubei Chen, Mingyang Li, Zengyi Li, Brent Yi, Yann LeCun, Yi Ma:
Unsupervised Learning of Structured Representation via Closed-Loop Transcription. CPAL 2024: 440-457 - [c186]Shengbang Tong, Zhuang Liu, Yuexiang Zhai, Yi Ma, Yann LeCun, Saining Xie:
Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs. CVPR 2024: 9568-9578 - [c185]Amir Bar, Arya Bakhtiar, Danny Tran, Antonio Loquercio, Jathushan Rajasegaran, Yann LeCun, Amir Globerson, Trevor Darrell:
EgoPet: Egomotion and Interaction Data from an Animal's Perspective. ECCV (37) 2024: 377-394 - [c184]Xiaoxin He, Xavier Bresson, Thomas Laurent, Adam Perold, Yann LeCun, Bryan Hooi:
Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning. ICLR 2024 - [c183]Grégoire Mialon, Clémentine Fourrier, Thomas Wolf, Yann LeCun, Thomas Scialom:
GAIA: a benchmark for General AI Assistants. ICLR 2024 - [c182]Randall Balestriero, Yann LeCun:
How Learning by Reconstruction Produces Uninformative Features For Perception. ICML 2024: 2566-2585 - [c181]Amir Bar, Florian Bordes, Assaf Shocher, Mido Assran, Pascal Vincent, Nicolas Ballas, Trevor Darrell, Amir Globerson, Yann LeCun:
Stochastic positional embeddings improve masked image modeling. ICML 2024: 2944-2958 - [c180]Ori Press, Ravid Shwartz-Ziv, Yann LeCun, Matthias Bethge:
The Entropy Enigma: Success and Failure of Entropy Minimization. ICML 2024: 41064-41085 - [c179]Xiaoxin He, Yijun Tian, Yifei Sun, Nitesh V. Chawla, Thomas Laurent, Yann LeCun, Xavier Bresson, Bryan Hooi:
G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering. NeurIPS 2024 - [c178]Peter Tong, Ellis Brown, Penghao Wu, Sanghyun Woo, Adithya Iyer, Sai Charitha Akula, Shusheng Yang, Jihan Yang, Manoj Middepogu, Ziteng Wang, Xichen Pan, Rob Fergus, Yann LeCun, Saining Xie:
Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs. NeurIPS 2024 - [c177]Simon Zhai, Hao Bai, Zipeng Lin, Jiayi Pan, Peter Tong, Yifei Zhou, Alane Suhr, Saining Xie, Yann LeCun, Yi Ma, Sergey Levine:
Fine-Tuning Large Vision-Language Models as Decision-Making Agents via Reinforcement Learning. NeurIPS 2024 - [i149]Shengbang Tong, Zhuang Liu, Yuexiang Zhai, Yi Ma, Yann LeCun, Saining Xie:
Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs. CoRR abs/2401.06209 (2024) - [i148]Randall Balestriero, Yann LeCun:
Fast and Exact Enumeration of Deep Networks Partitions Regions. CoRR abs/2401.11188 (2024) - [i147]Xiaoxin He, Yijun Tian, Yifei Sun, Nitesh V. Chawla, Thomas Laurent, Yann LeCun, Xavier Bresson, Bryan Hooi:
G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering. CoRR abs/2402.07630 (2024) - [i146]Randall Balestriero, Yann LeCun:
Learning by Reconstruction Produces Uninformative Features For Perception. CoRR abs/2402.11337 (2024) - [i145]Quentin Garrido, Mahmoud Assran, Nicolas Ballas, Adrien Bardes, Laurent Najman, Yann LeCun:
Learning and Leveraging World Models in Visual Representation Learning. CoRR abs/2403.00504 (2024) - [i144]Adrien Bardes, Quentin Garrido, Jean Ponce, Xinlei Chen, Michael G. Rabbat, Yann LeCun, Mahmoud Assran, Nicolas Ballas:
Revisiting Feature Prediction for Learning Visual Representations from Video. CoRR abs/2404.08471 (2024) - [i143]Amir Bar, Arya Bakhtiar, Danny Tran, Antonio Loquercio, Jathushan Rajasegaran, Yann LeCun, Amir Globerson, Trevor Darrell:
EgoPet: Egomotion and Interaction Data from an Animal's Perspective. CoRR abs/2404.09991 (2024) - [i142]Théo Moutakanni, Piotr Bojanowski, Guillaume Chassagnon, Céline Hudelot, Armand Joulin, Yann LeCun, Matthew J. Muckley, Maxime Oquab, Marie-Pierre Revel, Maria Vakalopoulou:
Advancing human-centric AI for robust X-ray analysis through holistic self-supervised learning. CoRR abs/2405.01469 (2024) - [i141]Ori Press, Ravid Shwartz-Ziv, Yann LeCun, Matthias Bethge:
The Entropy Enigma: Success and Failure of Entropy Minimization. CoRR abs/2405.05012 (2024) - [i140]Yuexiang Zhai, Hao Bai, Zipeng Lin, Jiayi Pan, Shengbang Tong, Yifei Zhou, Alane Suhr, Saining Xie, Yann LeCun, Yi Ma, Sergey Levine:
Fine-Tuning Large Vision-Language Models as Decision-Making Agents via Reinforcement Learning. CoRR abs/2405.10292 (2024) - [i139]Adrien Basdevant, Camille François, Victor Storchan, Kevin Bankston, Ayah Bdeir, Brian Behlendorf, Mérouane Debbah, Sayash Kapoor, Yann LeCun, Mark Surman, Helen King-Turvey, Nathan Lambert, Stefano Maffulli, Nik Marda, Govind Shivkumar, Justine Tunney:
Towards a Framework for Openness in Foundation Models: Proceedings from the Columbia Convening on Openness in Artificial Intelligence. CoRR abs/2405.15802 (2024) - [i138]Nicklas Hansen, Jyothir S. V, Vlad Sobal, Yann LeCun, Xiaolong Wang, Hao Su:
Hierarchical World Models as Visual Whole-Body Humanoid Controllers. CoRR abs/2405.18418 (2024) - [i137]Rylan Schaeffer, Victor Lecomte, Dhruv Bhandarkar Pai, Andres Carranza, Berivan Isik, Alyssa Unell, Mikail Khona, Thomas E. Yerxa, Yann LeCun, SueYeon Chung, Andrey Gromov, Ravid Shwartz-Ziv, Sanmi Koyejo:
Towards an Improved Understanding and Utilization of Maximum Manifold Capacity Representations. CoRR abs/2406.09366 (2024) - [i136]Ravid Shwartz-Ziv, Micah Goldblum, Arpit Bansal, C. Bayan Bruss, Yann LeCun, Andrew Gordon Wilson:
Just How Flexible are Neural Networks in Practice? CoRR abs/2406.11463 (2024) - [i135]Shengbang Tong, Ellis Brown, Penghao Wu, Sanghyun Woo, Manoj Middepogu, Sai Charitha Akula, Jihan Yang, Shusheng Yang, Adithya Iyer, Xichen Pan, Austin Wang, Rob Fergus, Yann LeCun, Saining Xie:
Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs. CoRR abs/2406.16860 (2024) - [i134]Colin White, Samuel Dooley, Manley Roberts, Arka Pal, Benjamin Feuer, Siddhartha Jain, Ravid Shwartz-Ziv, Neel Jain, Khalid Saifullah, Siddartha Naidu, Chinmay Hegde, Yann LeCun, Tom Goldstein, Willie Neiswanger, Micah Goldblum:
LiveBench: A Challenging, Contamination-Free LLM Benchmark. CoRR abs/2406.19314 (2024) - [i133]Vlad Sobal, Mark Ibrahim, Randall Balestriero, Vivien Cabannes, Diane Bouchacourt, Pietro Astolfi, Kyunghyun Cho, Yann LeCun:
𝕏-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs. CoRR abs/2407.18134 (2024) - [i132]Alex N. Wang, Christopher Hoang, Yuwen Xiong, Yann LeCun, Mengye Ren:
PooDLe: Pooled and dense self-supervised learning from naturalistic videos. CoRR abs/2408.11208 (2024) - [i131]Jan Witowski, Ken Zeng, Joseph Cappadona, Jailan Elayoubi, Elena Diana Chiru, Nancy Chan, Young-Joon Kang, Frederick Howard, Irina Ostrovnaya, Carlos Fernandez-Granda, Freya Schnabel, Ugur Ozerdem, Kangning Liu, Zoe Steinsnyder, Nitya Thakore, Mohammad Sadic, Frank Yeung, Elisa Liu, Theodore Hill, Benjamin Swett, Danielle Rigau, Andrew Clayburn, Valerie Speirs, Marcus Vetter, Lina Sojak, Simone Muenst Soysal, Daniel Baumhoer, Khalil Choucair, Yu Zong, Lina Daoud, Anas Saad, Waleed Abdulsattar, Rafic Beydoun, Jia-Wern Pan, Haslina Makmur, Soo-Hwang Teo, Linda Ma Pak, Victor Angel, Dovile Zilenaite-Petrulaitiene, Arvydas Laurinavicius, Natalie Klar, Brian Piening, Carlo Bifulco, Sun-Young Jun, Jae Pak Yi, Su Hyun Lim, Adam Brufsky, Francisco J. Esteva, Lajos Pusztai, Yann LeCun, Krzysztof J. Geras:
Multi-modal AI for comprehensive breast cancer prognostication. CoRR abs/2410.21256 (2024) - [i130]Md Rifat Arefin, Gopeshh Subbaraj, Nicolas Gontier, Yann LeCun, Irina Rish, Ravid Shwartz-Ziv, Christopher Pal:
Seq-VCR: Preventing Collapse in Intermediate Transformer Representations for Enhanced Reasoning. CoRR abs/2411.02344 (2024) - [i129]Gaoyue Zhou, Hengkai Pan, Yann LeCun, Lerrel Pinto:
DINO-WM: World Models on Pre-trained Visual Features enable Zero-shot Planning. CoRR abs/2411.04983 (2024) - [i128]Deep Chakraborty, Yann LeCun, Tim G. J. Rudner, Erik G. Learned-Miller:
Improving Pre-Trained Self-Supervised Embeddings Through Effective Entropy Maximization. CoRR abs/2411.15931 (2024) - [i127]Raktim Gautam Goswami, Prashanth Krishnamurthy, Yann LeCun, Farshad Khorrami:
RoboPEPP: Vision-Based Robot Pose and Joint Angle Estimation through Embedding Predictive Pre-Training. CoRR abs/2411.17662 (2024) - [i126]Amir Bar, Gaoyue Zhou, Danny Tran, Trevor Darrell, Yann LeCun:
Navigation World Models. CoRR abs/2412.03572 (2024) - [i125]Tal Zeevi, Ravid Shwartz-Ziv, Yann LeCun, Lawrence H. Staib, John A. Onofrey:
Rate-In: Information-Driven Adaptive Dropout Rates for Improved Inference-Time Uncertainty Estimation. CoRR abs/2412.07169 (2024) - [i124]Oscar Skean, Md Rifat Arefin, Yann LeCun, Ravid Shwartz-Ziv:
Does Representation Matter? Exploring Intermediate Layers in Large Language Models. CoRR abs/2412.09563 (2024) - [i123]Katrina Drozdov, Ravid Shwartz-Ziv, Yann LeCun:
Video Representation Learning with Joint-Embedding Predictive Architectures. CoRR abs/2412.10925 (2024) - [i122]Shengbang Tong, David Fan, Jiachen Zhu, Yunyang Xiong, Xinlei Chen, Koustuv Sinha, Michael Rabbat, Yann LeCun, Saining Xie, Zhuang Liu:
MetaMorph: Multimodal Understanding and Generation via Instruction Tuning. CoRR abs/2412.14164 (2024) - 2023
- [j45]Jacob Browning, Yann LeCun:
Language, common sense, and the Winograd schema challenge. Artif. Intell. 325: 104031 (2023) - [j44]Yubei Chen, Adrien Bardes, Zengyi Li, Yann LeCun:
Bag of Image Patch Embedding Behind the Success of Self-Supervised Learning. Trans. Mach. Learn. Res. 2023 (2023) - [j43]Grégoire Mialon, Roberto Dessì, Maria Lomeli, Christoforos Nalmpantis, Ramakanth Pasunuru, Roberta Raileanu, Baptiste Rozière, Timo Schick, Jane Dwivedi-Yu, Asli Celikyilmaz, Edouard Grave, Yann LeCun, Thomas Scialom:
Augmented Language Models: a Survey. Trans. Mach. Learn. Res. 2023 (2023) - [j42]Shraman Pramanick, Li Jing, Sayan Nag, Jiachen Zhu, Hardik Shah, Yann LeCun, Rama Chellappa:
VoLTA: Vision-Language Transformer with Weakly-Supervised Local-Feature Alignment. Trans. Mach. Learn. Res. 2023 (2023) - [c176]Ying Wang, Jonas Pfeiffer, Nicolas Carion, Yann LeCun, Aishwarya Kamath:
Adapting Grounded Visual Question Answering Models to Low Resource Languages. CVPR Workshops 2023: 2596-2605 - [c175]Mahmoud Assran, Quentin Duval, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Michael G. Rabbat, Yann LeCun, Nicolas Ballas:
Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture. CVPR 2023: 15619-15629 - [c174]Randall Balestriero, Yann LeCun:
Fast and Exact Enumeration of Deep Networks Partitions Regions. ICASSP 2023: 1-5 - [c173]Randall Balestriero, Yann LeCun:
Police: Provably Optimal Linear Constraint Enforcement For Deep Neural Networks. ICASSP 2023: 1-5 - [c172]Vivien Cabannes, Léon Bottou, Yann LeCun, Randall Balestriero:
Active Self-Supervised Learning: A Few Low-Cost Relationships Are All You Need. ICCV 2023: 16228-16237 - [c171]Yubei Chen, Zeyu Yun, Yi Ma, Bruno A. Olshausen, Yann LeCun:
Minimalistic Unsupervised Representation Learning with the Sparse Manifold Transform. ICLR 2023 - [c170]Quentin Garrido, Yubei Chen, Adrien Bardes, Laurent Najman, Yann LeCun:
On the duality between contrastive and non-contrastive self-supervised learning. ICLR 2023 - [c169]Vivien Cabannes, Bobak Toussi Kiani, Randall Balestriero, Yann LeCun, Alberto Bietti:
The SSL Interplay: Augmentations, Inductive Bias, and Generalization. ICML 2023: 3252-3298 - [c168]Quentin Garrido, Randall Balestriero, Laurent Najman, Yann LeCun:
RankMe: Assessing the Downstream Performance of Pretrained Self-Supervised Representations by Their Rank. ICML 2023: 10929-10974 - [c167]Quentin Garrido, Laurent Najman, Yann LeCun:
Self-supervised learning of Split Invariant Equivariant representations. ICML 2023: 10975-10996 - [c166]Xiaoxin He, Bryan Hooi, Thomas Laurent, Adam Perold, Yann LeCun, Xavier Bresson:
A Generalization of ViT/MLP-Mixer to Graphs. ICML 2023: 12724-12745 - [c165]Ido Ben-Shaul, Ravid Shwartz-Ziv, Tomer Galanti, Shai Dekel, Yann LeCun:
Reverse Engineering Self-Supervised Learning. NeurIPS 2023 - [c164]Grégoire Mialon, Quentin Garrido, Hannah Lawrence, Danyal Rehman, Yann LeCun, Bobak T. Kiani:
Self-Supervised Learning with Lie Symmetries for Partial Differential Equations. NeurIPS 2023 - [c163]Ravid Shwartz-Ziv, Randall Balestriero, Kenji Kawaguchi, Tim G. J. Rudner, Yann LeCun:
An Information Theory Perspective on Variance-Invariance-Covariance Regularization. NeurIPS 2023 - [c162]Jiayun Wang, Yubei Chen, Stella X. Yu, Brian Cheung, Yann LeCun:
Compact and Optimal Deep Learning with Recurrent Parameter Generators. WACV 2023: 3889-3899 - [i121]Mahmoud Assran, Quentin Duval, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Michael G. Rabbat, Yann LeCun, Nicolas Ballas:
Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture. CoRR abs/2301.08243 (2023) - [i120]Shoaib Ahmed Siddiqui, David Krueger, Yann LeCun, Stéphane Deny:
Blockwise Self-Supervised Learning at Scale. CoRR abs/2302.01647 (2023) - [i119]Vivien Cabannes, Bobak Toussi Kiani, Randall Balestriero, Yann LeCun, Alberto Bietti:
The SSL Interplay: Augmentations, Inductive Bias, and Generalization. CoRR abs/2302.02774 (2023) - [i118]Grégoire Mialon, Roberto Dessì, Maria Lomeli, Christoforos Nalmpantis, Ramakanth Pasunuru, Roberta Raileanu, Baptiste Rozière, Timo Schick, Jane Dwivedi-Yu, Asli Celikyilmaz, Edouard Grave, Yann LeCun, Thomas Scialom:
Augmented Language Models: a Survey. CoRR abs/2302.07842 (2023) - [i117]Quentin Garrido, Laurent Najman, Yann LeCun:
Self-supervised learning of Split Invariant Equivariant representations. CoRR abs/2302.10283 (2023) - [i116]Ravid Shwartz-Ziv, Randall Balestriero, Kenji Kawaguchi, Tim G. J. Rudner, Yann LeCun:
An Information-Theoretic Perspective on Variance-Invariance-Covariance Regularization. CoRR abs/2303.00633 (2023) - [i115]Vivien Cabannes, Léon Bottou, Yann LeCun, Randall Balestriero:
Active Self-Supervised Learning: A Few Low-Cost Relationships Are All You Need. CoRR abs/2303.15256 (2023) - [i114]Shengbang Tong, Yubei Chen, Yi Ma, Yann LeCun:
EMP-SSL: Towards Self-Supervised Learning in One Training Epoch. CoRR abs/2304.03977 (2023) - [i113]Ravid Shwartz-Ziv, Yann LeCun:
To Compress or Not to Compress - Self-Supervised Learning and Information Theory: A Review. CoRR abs/2304.09355 (2023) - [i112]Randall Balestriero, Mark Ibrahim, Vlad Sobal, Ari Morcos, Shashank Shekhar, Tom Goldstein, Florian Bordes, Adrien Bardes, Grégoire Mialon, Yuandong Tian, Avi Schwarzschild, Andrew Gordon Wilson, Jonas Geiping, Quentin Garrido, Pierre Fernandez, Amir Bar, Hamed Pirsiavash, Yann LeCun, Micah Goldblum:
A Cookbook of Self-Supervised Learning. CoRR abs/2304.12210 (2023) - [i111]Ido Ben-Shaul, Ravid Shwartz-Ziv, Tomer Galanti, Shai Dekel, Yann LeCun:
Reverse Engineering Self-Supervised Learning. CoRR abs/2305.15614 (2023) - [i110]Anna Dawid, Yann LeCun:
Introduction to Latent Variable Energy-Based Models: A Path Towards Autonomous Machine Intelligence. CoRR abs/2306.02572 (2023) - [i109]Jiachen Zhu, Ravid Shwartz-Ziv, Yubei Chen, Yann LeCun:
Variance-Covariance Regularization Improves Representation Learning. CoRR abs/2306.13292 (2023) - [i108]Grégoire Mialon, Quentin Garrido, Hannah Lawrence, Danyal Rehman, Yann LeCun, Bobak Toussi Kiani:
Self-Supervised Learning with Lie Symmetries for Partial Differential Equations. CoRR abs/2307.05432 (2023) - [i107]Adrien Bardes, Jean Ponce, Yann LeCun:
MC-JEPA: A Joint-Embedding Predictive Architecture for Self-Supervised Learning of Motion and Content Features. CoRR abs/2307.12698 (2023) - [i106]Amir Bar, Florian Bordes, Assaf Shocher, Mahmoud Assran, Pascal Vincent, Nicolas Ballas, Trevor Darrell, Amir Globerson, Yann LeCun:
Predicting masked tokens in stochastic locations improves masked image modeling. CoRR abs/2308.00566 (2023) - [i105]Zeyu Yun, Juexiao Zhang, Bruno A. Olshausen, Yann LeCun, Yubei Chen:
URLOST: Unsupervised Representation Learning without Stationarity or Topology. CoRR abs/2310.04496 (2023) - [i104]Grégoire Mialon, Clémentine Fourrier, Craig Swift, Thomas Wolf, Yann LeCun, Thomas Scialom:
GAIA: a benchmark for General AI Assistants. CoRR abs/2311.12983 (2023) - [i103]Jyothir S. V, Siddhartha Jalagam, Yann LeCun, Vlad Sobal:
Gradient-based Planning with World Models. CoRR abs/2312.17227 (2023) - 2022
- [j41]Yutaka Matsuo, Yann LeCun, Maneesh Sahani, Doina Precup, David Silver, Masashi Sugiyama, Eiji Uchibe, Jun Morimoto:
Deep learning, reinforcement learning, and world models. Neural Networks 152: 267-275 (2022) - [j40]Katrina Evtimova, Yann LeCun:
Sparse Coding with Multi-layer Decoders using Variance Regularization. Trans. Mach. Learn. Res. 2022 (2022) - [c161]Chun-Hsiao Yeh, Cheng-Yao Hong, Yen-Chi Hsu, Tyng-Luh Liu, Yubei Chen, Yann LeCun:
Decoupled Contrastive Learning. ECCV (26) 2022: 668-684 - [c160]Adrien Bardes, Jean Ponce, Yann LeCun:
VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning. ICLR 2022 - [c159]Li Jing, Pascal Vincent, Yann LeCun, Yuandong Tian:
Understanding Dimensional Collapse in Contrastive Self-supervised Learning. ICLR 2022 - [c158]Randall Balestriero, Léon Bottou, Yann LeCun:
The Effects of Regularization and Data Augmentation are Class Dependent. NeurIPS 2022 - [c157]Randall Balestriero, Yann LeCun:
Contrastive and Non-Contrastive Self-Supervised Learning Recover Global and Local Spectral Embedding Methods. NeurIPS 2022 - [c156]Randall Balestriero, Ishan Misra, Yann LeCun:
A Data-Augmentation Is Worth A Thousand Samples: Analytical Moments And Sampling-Free Training. NeurIPS 2022 - [c155]Adrien Bardes, Jean Ponce, Yann LeCun:
VICRegL: Self-Supervised Learning of Local Visual Features. NeurIPS 2022 - [c154]Zi-Yi Dou, Aishwarya Kamath, Zhe Gan, Pengchuan Zhang, Jianfeng Wang, Linjie Li, Zicheng Liu, Ce Liu, Yann LeCun, Nanyun Peng, Jianfeng Gao, Lijuan Wang:
Coarse-to-Fine Vision-Language Pre-training with Fusion in the Backbone. NeurIPS 2022 - [c153]Bobak Toussi Kiani, Randall Balestriero, Yann LeCun, Seth Lloyd:
projUNN: efficient method for training deep networks with unitary matrices. NeurIPS 2022 - [c152]Ravid Shwartz-Ziv, Micah Goldblum, Hossein Souri, Sanyam Kapoor, Chen Zhu, Yann LeCun, Andrew Gordon Wilson:
Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors. NeurIPS 2022 - [i102]Zengyi Li, Yubei Chen, Yann LeCun, Friedrich T. Sommer:
Neural Manifold Clustering and Embedding. CoRR abs/2201.10000 (2022) - [i101]Randall Balestriero, Ishan Misra, Yann LeCun:
A Data-Augmentation Is Worth A Thousand Samples: Exact Quantification From Analytical Augmented Sample Moments. CoRR abs/2202.08325 (2022) - [i100]Bobak Toussi Kiani, Randall Balestriero, Yann LeCun, Seth Lloyd:
projUNN: efficient method for training deep networks with unitary matrices. CoRR abs/2203.05483 (2022) - [i99]Randall Balestriero, Léon Bottou, Yann LeCun:
The Effects of Regularization and Data Augmentation are Class Dependent. CoRR abs/2204.03632 (2022) - [i98]Vlad Sobal, Alfredo Canziani, Nicolas Carion, Kyunghyun Cho, Yann LeCun:
Separating the World and Ego Models for Self-Driving. CoRR abs/2204.07184 (2022) - [i97]Ravid Shwartz-Ziv, Micah Goldblum, Hossein Souri, Sanyam Kapoor, Chen Zhu, Yann LeCun, Andrew Gordon Wilson:
Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors. CoRR abs/2205.10279 (2022) - [i96]Randall Balestriero, Yann LeCun:
Contrastive and Non-Contrastive Self-Supervised Learning Recover Global and Local Spectral Embedding Methods. CoRR abs/2205.11508 (2022) - [i95]Quentin Garrido, Yubei Chen, Adrien Bardes, Laurent Najman, Yann LeCun:
On the duality between contrastive and non-contrastive self-supervised learning. CoRR abs/2206.02574 (2022) - [i94]Zi-Yi Dou, Aishwarya Kamath, Zhe Gan, Pengchuan Zhang, Jianfeng Wang, Linjie Li, Zicheng Liu, Ce Liu, Yann LeCun, Nanyun Peng, Jianfeng Gao, Lijuan Wang:
Coarse-to-Fine Vision-Language Pre-training with Fusion in the Backbone. CoRR abs/2206.07643 (2022) - [i93]Li Jing, Jiachen Zhu, Yann LeCun:
Masked Siamese ConvNets. CoRR abs/2206.07700 (2022) - [i92]Yubei Chen, Adrien Bardes, Zengyi Li, Yann LeCun:
Intra-Instance VICReg: Bag of Self-Supervised Image Patch Embedding. CoRR abs/2206.08954 (2022) - [i91]Jiachen Zhu, Rafael M. Moraes, Serkan Karakulak, Vlad Sobol, Alfredo Canziani, Yann LeCun:
TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning. CoRR abs/2206.10698 (2022) - [i90]Ravid Shwartz-Ziv, Randall Balestriero, Yann LeCun:
What Do We Maximize in Self-Supervised Learning? CoRR abs/2207.10081 (2022) - [i89]Wancong Zhang, Anthony GX-Chen, Vlad Sobal, Yann LeCun, Nicolas Carion:
Light-weight probing of unsupervised representations for Reinforcement Learning. CoRR abs/2208.12345 (2022) - [i88]Bobak Toussi Kiani, Randall Balestriero, Yubei Chen, Seth Lloyd, Yann LeCun:
Joint Embedding Self-Supervised Learning in the Kernel Regime. CoRR abs/2209.14884 (2022) - [i87]Grégoire Mialon, Randall Balestriero, Yann LeCun:
Variance Covariance Regularization Enforces Pairwise Independence in Self-Supervised Representations. CoRR abs/2209.14905 (2022) - [i86]Yubei Chen, Zeyu Yun, Yi Ma, Bruno A. Olshausen, Yann LeCun:
Minimalistic Unsupervised Learning with the Sparse Manifold Transform. CoRR abs/2209.15261 (2022) - [i85]Adrien Bardes, Jean Ponce, Yann LeCun:
VICRegL: Self-Supervised Learning of Local Visual Features. CoRR abs/2210.01571 (2022) - [i84]Quentin Garrido, Randall Balestriero, Laurent Najman, Yann LeCun:
RankMe: Assessing the downstream performance of pretrained self-supervised representations by their rank. CoRR abs/2210.02885 (2022) - [i83]Shraman Pramanick, Li Jing, Sayan Nag, Jiachen Zhu, Hardik Shah, Yann LeCun, Rama Chellappa:
VoLTA: Vision-Language Transformer with Weakly-Supervised Local-Feature Alignment. CoRR abs/2210.04135 (2022) - [i82]Anthony Zador, Blake A. Richards, Bence Ölveczky, Sean Escola, Yoshua Bengio, Kwabena Boahen, Matthew M. Botvinick, Dmitri B. Chklovskii, Anne Churchland, Claudia Clopath, James DiCarlo, Surya Ganguli, Jeff Hawkins, Konrad P. Körding, Alexei A. Koulakov, Yann LeCun, Timothy P. Lillicrap, Adam H. Marblestone, Bruno A. Olshausen, Alexandre Pouget, Cristina Savin, Terrence J. Sejnowski, Eero P. Simoncelli, Sara A. Solla, David Sussillo, Andreas S. Tolias, Doris Tsao:
Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution. CoRR abs/2210.08340 (2022) - [i81]Shengbang Tong, Xili Dai, Yubei Chen, Mingyang Li, Zengyi Li, Brent Yi, Yann LeCun, Yi Ma:
Unsupervised Learning of Structured Representations via Closed-Loop Transcription. CoRR abs/2210.16782 (2022) - [i80]Randall Balestriero, Yann LeCun:
POLICE: Provably Optimal Linear Constraint Enforcement for Deep Neural Networks. CoRR abs/2211.01340 (2022) - [i79]Vlad Sobal, Jyothir S. V, Siddhartha Jalagam, Nicolas Carion, Kyunghyun Cho, Yann LeCun:
Joint Embedding Predictive Architectures Focus on Slow Features. CoRR abs/2211.10831 (2022) - [i78]Xiaoxin He, Bryan Hooi, Thomas Laurent, Adam Perold, Yann LeCun, Xavier Bresson:
A Generalization of ViT/MLP-Mixer to Graphs. CoRR abs/2212.13350 (2022) - 2021
- [j39]Yoshua Bengio, Yann LeCun, Geoffrey E. Hinton:
Deep learning for AI. Commun. ACM 64(7): 58-65 (2021) - [j38]Baptiste Rozière, Morgane Rivière, Olivier Teytaud, Jérémy Rapin, Yann LeCun, Camille Couprie:
Inspirational Adversarial Image Generation. IEEE Trans. Image Process. 30: 4036-4045 (2021) - [c151]Zeyu Yun, Yubei Chen, Bruno A. Olshausen, Yann LeCun:
Transformer visualization via dictionary learning: contextualized embedding as a linear superposition of transformer factors. DeeLIO@NAACL-HLT 2021: 1-10 - [c150]Aishwarya Kamath, Mannat Singh, Yann LeCun, Gabriel Synnaeve, Ishan Misra, Nicolas Carion:
MDETR - Modulated Detection for End-to-End Multi-Modal Understanding. ICCV 2021: 1760-1770 - [c149]Jure Zbontar, Li Jing, Ishan Misra, Yann LeCun, Stéphane Deny:
Barlow Twins: Self-Supervised Learning via Redundancy Reduction. ICML 2021: 12310-12320 - [d1]Xiang Zhang, Junbo Zhao, Yann LeCun:
DBPedia. IEEE DataPort, 2021 - [i77]Jure Zbontar, Li Jing, Ishan Misra, Yann LeCun, Stéphane Deny:
Barlow Twins: Self-Supervised Learning via Redundancy Reduction. CoRR abs/2103.03230 (2021) - [i76]Zeyu Yun, Yubei Chen, Bruno A. Olshausen, Yann LeCun:
Transformer visualization via dictionary learning: contextualized embedding as a linear superposition of transformer factors. CoRR abs/2103.15949 (2021) - [i75]Aishwarya Kamath, Mannat Singh, Yann LeCun, Ishan Misra, Gabriel Synnaeve, Nicolas Carion:
MDETR - Modulated Detection for End-to-End Multi-Modal Understanding. CoRR abs/2104.12763 (2021) - [i74]Adrien Bardes, Jean Ponce, Yann LeCun:
VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning. CoRR abs/2105.04906 (2021) - [i73]Jiayun Wang, Yubei Chen, Stella X. Yu, Brian Cheung, Yann LeCun:
Recurrent Parameter Generators. CoRR abs/2107.07110 (2021) - [i72]Chun-Hsiao Yeh, Cheng-Yao Hong, Yen-Chi Hsu, Tyng-Luh Liu, Yubei Chen, Yann LeCun:
Decoupled Contrastive Learning. CoRR abs/2110.06848 (2021) - [i71]Li Jing, Pascal Vincent, Yann LeCun, Yuandong Tian:
Understanding Dimensional Collapse in Contrastive Self-supervised Learning. CoRR abs/2110.09348 (2021) - [i70]Randall Balestriero, Jerome Pesenti, Yann LeCun:
Learning in High Dimension Always Amounts to Extrapolation. CoRR abs/2110.09485 (2021) - [i69]Katrina Evtimova, Yann LeCun:
Sparse Coding with Multi-Layer Decoders using Variance Regularization. CoRR abs/2112.09214 (2021) - 2020
- [c148]Li Jing, Jure Zbontar, Yann LeCun:
Implicit Rank-Minimizing Autoencoder. NeurIPS 2020 - [i68]Li Jing, Jure Zbontar, Yann LeCun:
Implicit Rank-Minimizing Autoencoder. CoRR abs/2010.00679 (2020)
2010 – 2019
- 2019
- [c147]Huy V. Vo, Francis R. Bach, Minsu Cho, Kai Han, Yann LeCun, Patrick Pérez, Jean Ponce:
Unsupervised Image Matching and Object Discovery as Optimization. CVPR 2019: 8287-8296 - [c146]Mikael Henaff, Alfredo Canziani, Yann LeCun:
Model-Predictive Policy Learning with Uncertainty Regularization for Driving in Dense Traffic. ICLR (Poster) 2019 - [c145]Behnam Neyshabur, Zhiyuan Li, Srinadh Bhojanapalli, Yann LeCun, Nathan Srebro:
The role of over-parametrization in generalization of neural networks. ICLR (Poster) 2019 - [c144]Yann LeCun:
Deep Learning Hardware: Past, Present, and Future. ISSCC 2019: 12-19 - [i67]Mikael Henaff, Alfredo Canziani, Yann LeCun:
Model-Predictive Policy Learning with Uncertainty Regularization for Driving in Dense Traffic. CoRR abs/1901.02705 (2019) - [i66]Mohamed Ishmael Belghazi, Maxime Oquab, Yann LeCun, David Lopez-Paz:
Learning about an exponential amount of conditional distributions. CoRR abs/1902.08401 (2019) - [i65]Huy V. Vo, Francis R. Bach, Minsu Cho, Kai Han, Yann LeCun, Patrick Pérez, Jean Ponce:
Unsupervised Image Matching and Object Discovery as Optimization. CoRR abs/1904.03148 (2019) - [i64]Morgane Rivière, Olivier Teytaud, Jérémy Rapin, Yann LeCun, Camille Couprie:
Inspirational Adversarial Image Generation. CoRR abs/1906.11661 (2019) - 2018
- [c143]Du Tran, Heng Wang, Lorenzo Torresani, Jamie Ray, Yann LeCun, Manohar Paluri:
A Closer Look at Spatiotemporal Convolutions for Action Recognition. CVPR 2018: 6450-6459 - [c142]Othman Sbai, Mohamed Elhoseiny, Antoine Bordes, Yann LeCun, Camille Couprie:
DesIGN: Design Inspiration from Generative Networks. ECCV Workshops (3) 2018: 37-44 - [c141]Pauline Luc, Camille Couprie, Yann LeCun, Jakob Verbeek:
Predicting Future Instance Segmentation by Forecasting Convolutional Features. ECCV (9) 2018: 593-608 - [c140]Marco Baity-Jesi, Levent Sagun, Mario Geiger, Stefano Spigler, Gérard Ben Arous, Chiara Cammarota, Yann LeCun, Matthieu Wyart, Giulio Biroli:
Comparing Dynamics: Deep Neural Networks versus Glassy Systems. ICML 2018: 324-333 - [c139]Junbo Jake Zhao, Yoon Kim, Kelly Zhang, Alexander M. Rush, Yann LeCun:
Adversarially Regularized Autoencoders. ICML 2018: 5897-5906 - [c138]Zhilin Yang, Junbo Jake Zhao, Bhuwan Dhingra, Kaiming He, William W. Cohen, Ruslan Salakhutdinov, Yann LeCun:
GLoMo: Unsupervised Learning of Transferable Relational Graphs. NeurIPS 2018: 8964-8975 - [i63]Xiang Zhang, Yann LeCun:
Byte-Level Recursive Convolutional Auto-Encoder for Text. CoRR abs/1802.01817 (2018) - [i62]Marco Baity-Jesi, Levent Sagun, Mario Geiger, Stefano Spigler, Gérard Ben Arous, Chiara Cammarota, Yann LeCun, Matthieu Wyart, Giulio Biroli:
Comparing Dynamics: Deep Neural Networks versus Glassy Systems. CoRR abs/1803.06969 (2018) - [i61]Pauline Luc, Camille Couprie, Yann LeCun, Jakob Verbeek:
Predicting Future Instance Segmentations by Forecasting Convolutional Features. CoRR abs/1803.11496 (2018) - [i60]Othman Sbai, Mohamed Elhoseiny, Antoine Bordes, Yann LeCun, Camille Couprie:
DeSIGN: Design Inspiration from Generative Networks. CoRR abs/1804.00921 (2018) - [i59]Behnam Neyshabur, Zhiyuan Li, Srinadh Bhojanapalli, Yann LeCun, Nathan Srebro:
Towards Understanding the Role of Over-Parametrization in Generalization of Neural Networks. CoRR abs/1805.12076 (2018) - [i58]Aditya Ramesh, Yann LeCun:
Backpropagation for Implicit Spectral Densities. CoRR abs/1806.00499 (2018) - [i57]Zhilin Yang, Junbo Jake Zhao, Bhuwan Dhingra, Kaiming He, William W. Cohen, Ruslan Salakhutdinov, Yann LeCun:
GLoMo: Unsupervisedly Learned Relational Graphs as Transferable Representations. CoRR abs/1806.05662 (2018) - [i56]Xiang Zhang, Yann LeCun:
Adversarially-Trained Normalized Noisy-Feature Auto-Encoder for Text Generation. CoRR abs/1811.04201 (2018) - [i55]Aditya Ramesh, Youngduck Choi, Yann LeCun:
A Spectral Regularizer for Unsupervised Disentanglement. CoRR abs/1812.01161 (2018) - 2017
- [j37]Michael M. Bronstein, Joan Bruna, Yann LeCun, Arthur Szlam, Pierre Vandergheynst:
Geometric Deep Learning: Going beyond Euclidean data. IEEE Signal Process. Mag. 34(4): 18-42 (2017) - [c137]Xiang Zhang, Yann LeCun:
Universum Prescription: Regularization Using Unlabeled Data. AAAI 2017: 2907-2913 - [c136]Alexis Conneau, Holger Schwenk, Loïc Barrault, Yann LeCun:
Very Deep Convolutional Networks for Text Classification. EACL (1) 2017: 1107-1116 - [c135]Pauline Luc, Natalia Neverova, Camille Couprie, Jakob Verbeek, Yann LeCun:
Predicting Deeper into the Future of Semantic Segmentation. ICCV 2017: 648-657 - [c134]Pratik Chaudhari, Anna Choromanska, Stefano Soatto, Yann LeCun, Carlo Baldassi, Christian Borgs, Jennifer T. Chayes, Levent Sagun, Riccardo Zecchina:
Entropy-SGD: Biasing Gradient Descent Into Wide Valleys. ICLR (Poster) 2017 - [c133]Mikael Henaff, Jason Weston, Arthur Szlam, Antoine Bordes, Yann LeCun:
Tracking the World State with Recurrent Entity Networks. ICLR (Poster) 2017 - [c132]Junbo Jake Zhao, Michaël Mathieu, Yann LeCun:
Energy-based Generative Adversarial Networks. ICLR (Poster) 2017 - [c131]Li Jing, Yichen Shen, Tena Dubcek, John Peurifoy, Scott A. Skirlo, Yann LeCun, Max Tegmark, Marin Soljacic:
Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNNs. ICML 2017: 1733-1741 - [i54]Natalia Neverova, Pauline Luc, Camille Couprie, Jakob Verbeek, Yann LeCun:
Predicting Deeper into the Future of Semantic Segmentation. CoRR abs/1703.07684 (2017) - [i53]Mikael Henaff, William F. Whitney, Yann LeCun:
Model-Based Planning in Discrete Action Spaces. CoRR abs/1705.07177 (2017) - [i52]Junbo Jake Zhao, Yoon Kim, Kelly Zhang, Alexander M. Rush, Yann LeCun:
Adversarially Regularized Autoencoders for Generating Discrete Structures. CoRR abs/1706.04223 (2017) - [i51]Xiang Zhang, Yann LeCun:
Which Encoding is the Best for Text Classification in Chinese, English, Japanese and Korean? CoRR abs/1708.02657 (2017) - [i50]Cinna Wu, Mark Tygert, Yann LeCun:
Hierarchical loss for classification. CoRR abs/1709.01062 (2017) - [i49]Mikael Henaff, Junbo Jake Zhao, Yann LeCun:
Prediction Under Uncertainty with Error-Encoding Networks. CoRR abs/1711.04994 (2017) - [i48]Du Tran, Heng Wang, Lorenzo Torresani, Jamie Ray, Yann LeCun, Manohar Paluri:
A Closer Look at Spatiotemporal Convolutions for Action Recognition. CoRR abs/1711.11248 (2017) - 2016
- [j36]Jure Zbontar, Yann LeCun:
Stereo Matching by Training a Convolutional Neural Network to Compare Image Patches. J. Mach. Learn. Res. 17: 65:1-65:32 (2016) - [j35]Mark Tygert, Joan Bruna, Soumith Chintala, Yann LeCun, Serkan Piantino, Arthur Szlam:
A Mathematical Motivation for Complex-Valued Convolutional Networks. Neural Comput. 28(5): 815-825 (2016) - [c130]Tom Sercu, Christian Puhrsch, Brian Kingsbury, Yann LeCun:
Very deep multilingual convolutional neural networks for LVCSR. ICASSP 2016: 4955-4959 - [c129]Anna Choromanska, Krzysztof Choromanski, Mariusz Bojarski, Tony Jebara, Sanjiv Kumar, Yann LeCun:
Binary embeddings with structured hashed projections. ICML 2016: 344-353 - [c128]Mikael Henaff, Arthur Szlam, Yann LeCun:
Recurrent Orthogonal Networks and Long-Memory Tasks. ICML 2016: 2034-2042 - [c127]Michaël Mathieu, Junbo Jake Zhao, Pablo Sprechmann, Aditya Ramesh, Yann LeCun:
Disentangling factors of variation in deep representation using adversarial training. NIPS 2016: 5041-5049 - [c126]Joan Bruna, Pablo Sprechmann, Yann LeCun:
Super-Resolution with Deep Convolutional Sufficient Statistics. ICLR (Poster) 2016 - [c125]Michaël Mathieu, Camille Couprie, Yann LeCun:
Deep multi-scale video prediction beyond mean square error. ICLR (Poster) 2016 - [e7]Yoshua Bengio, Yann LeCun:
4th International Conference on Learning Representations, ICLR 2016, San Juan, Puerto Rico, May 2-4, 2016, Conference Track Proceedings. 2016 [contents] - [i47]Mikael Henaff, Arthur Szlam, Yann LeCun:
Orthogonal RNNs and Long-Memory Tasks. CoRR abs/1602.06662 (2016) - [i46]Peter J. Dugan, Christopher W. Clark, Yann André LeCun, Sofie M. Van Parijs:
Phase 1: DCL System Research Using Advanced Approaches for Land-based or Ship-based Real-Time Recognition and Localization of Marine Mammals - HPC System Implementation. CoRR abs/1605.00971 (2016) - [i45]Peter J. Dugan, Christopher W. Clark, Yann André LeCun, Sofie M. Van Parijs:
Phase 2: DCL System Using Deep Learning Approaches for Land-based or Ship-based Real-Time Recognition and Localization of Marine Mammals - Machine Learning Detection Algorithms. CoRR abs/1605.00972 (2016) - [i44]Peter J. Dugan, Christopher W. Clark, Yann André LeCun, Sofie M. Van Parijs:
Phase 4: DCL System Using Deep Learning Approaches for Land-Based or Ship-Based Real-Time Recognition and Localization of Marine Mammals - Distributed Processing and Big Data Applications. CoRR abs/1605.00982 (2016) - [i43]Peter J. Dugan, Christopher W. Clark, Yann André LeCun, Sofie M. Van Parijs:
Phase 3: DCL System Using Deep Learning Approaches for Land-based or Ship-based Real-Time Recognition and Localization of Marine Mammals - Bioacoustic Applicaitons. CoRR abs/1605.00983 (2016) - [i42]Kevin Jarrett, Koray Kavukcuoglu, Karol Gregor, Yann LeCun:
What is the Best Feature Learning Procedure in Hierarchical Recognition Architectures? CoRR abs/1606.01535 (2016) - [i41]Alexis Conneau, Holger Schwenk, Loïc Barrault, Yann LeCun:
Very Deep Convolutional Networks for Natural Language Processing. CoRR abs/1606.01781 (2016) - [i40]Artem Provodin, Liila Torabi, Beat Flepp, Yann LeCun, Michael Sergio, Lawrence D. Jackel, Urs Muller, Jure Zbontar:
Fast Incremental Learning for Off-Road Robot Navigation. CoRR abs/1606.08057 (2016) - [i39]Junbo Jake Zhao, Michaël Mathieu, Yann LeCun:
Energy-based Generative Adversarial Network. CoRR abs/1609.03126 (2016) - [i38]Yacine Jernite, Anna Choromanska, David A. Sontag, Yann LeCun:
Simultaneous Learning of Trees and Representations for Extreme Classification, with Application to Language Modeling. CoRR abs/1610.04658 (2016) - [i37]Pratik Chaudhari, Anna Choromanska, Stefano Soatto, Yann LeCun, Carlo Baldassi, Christian Borgs, Jennifer T. Chayes, Levent Sagun, Riccardo Zecchina:
Entropy-SGD: Biasing Gradient Descent Into Wide Valleys. CoRR abs/1611.01838 (2016) - [i36]Michaël Mathieu, Junbo Jake Zhao, Pablo Sprechmann, Aditya Ramesh, Yann LeCun:
Disentangling factors of variation in deep representations using adversarial training. CoRR abs/1611.03383 (2016) - [i35]Levent Sagun, Léon Bottou, Yann LeCun:
Singularity of the Hessian in Deep Learning. CoRR abs/1611.07476 (2016) - [i34]Michael M. Bronstein, Joan Bruna, Yann LeCun, Arthur Szlam, Pierre Vandergheynst:
Geometric deep learning: going beyond Euclidean data. CoRR abs/1611.08097 (2016) - [i33]Mikael Henaff, Jason Weston, Arthur Szlam, Antoine Bordes, Yann LeCun:
Tracking the World State with Recurrent Entity Networks. CoRR abs/1612.03969 (2016) - 2015
- [j34]Marc'Aurelio Ranzato, Geoffrey E. Hinton, Yann LeCun:
Guest Editorial: Deep Learning. Int. J. Comput. Vis. 113(1): 1-2 (2015) - [j33]Yann LeCun, Yoshua Bengio, Geoffrey E. Hinton:
Deep learning. Nat. 521(7553): 436-444 (2015) - [c124]Anna Choromanska, Mikael Henaff, Michaël Mathieu, Gérard Ben Arous, Yann LeCun:
The Loss Surfaces of Multilayer Networks. AISTATS 2015 - [c123]Anna Choromanska, Yann LeCun, Gérard Ben Arous:
Open Problem: The landscape of the loss surfaces of multilayer networks. COLT 2015: 1756-1760 - [c122]Jonathan Tompson, Ross Goroshin, Arjun Jain, Yann LeCun, Christoph Bregler:
Efficient object localization using Convolutional Networks. CVPR 2015: 648-656 - [c121]Jure Zbontar, Yann LeCun:
Computing the stereo matching cost with a convolutional neural network. CVPR 2015: 1592-1599 - [c120]Yann LeCun:
Deep learning & convolutional networks. Hot Chips Symposium 2015: 1-95 - [c119]Pablo Sprechmann, Joan Bruna, Yann LeCun:
Audio Source Separation with Discriminative Scattering Networks. LVA/ICA 2015: 259-267 - [c118]Joan Bruna, Pablo Sprechmann, Yann LeCun:
Source separation with scattering Non-Negative Matrix Factorization. ICASSP 2015: 1876-1880 - [c117]Ross Goroshin, Joan Bruna, Jonathan Tompson, David Eigen, Yann LeCun:
Unsupervised Learning of Spatiotemporally Coherent Metrics. ICCV 2015: 4086-4093 - [c116]Xiang Zhang, Junbo Jake Zhao, Yann LeCun:
Character-level Convolutional Networks for Text Classification. NIPS 2015: 649-657 - [c115]Sixin Zhang, Anna Choromanska, Yann LeCun:
Deep learning with Elastic Averaging SGD. NIPS 2015: 685-693 - [c114]Ross Goroshin, Michaël Mathieu, Yann LeCun:
Learning to Linearize Under Uncertainty. NIPS 2015: 1234-1242 - [c113]Ross Goroshin, Joan Bruna, Jonathan Tompson, David Eigen, Yann LeCun:
Unsupervised Feature Learning from Temporal Data. ICLR (Workshop) 2015 - [c112]Levent Sagun, V. Ugur Güney, Yann LeCun:
Explorations on high dimensional landscapes. ICLR (Workshop) 2015 - [c111]Pablo Sprechmann, Joan Bruna, Yann LeCun:
Audio Source Separation with Discriminative Scattering Networks. ICLR (Workshop) 2015 - [c110]Nicolas Vasilache, Jeff Johnson, Michaël Mathieu, Soumith Chintala, Serkan Piantino, Yann LeCun:
Fast Convolutional Nets With fbfft: A GPU Performance Evaluation. ICLR 2015 - [c109]Sixin Zhang, Anna Choromanska, Yann LeCun:
Deep learning with Elastic Averaging SGD. ICLR (Workshop) 2015 - [e6]Yoshua Bengio, Yann LeCun:
3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7-9, 2015, Conference Track Proceedings. 2015 [contents] - [e5]Yoshua Bengio, Yann LeCun:
3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7-9, 2015, Workshop Track Proceedings. 2015 [contents] - [i32]Xiang Zhang, Yann LeCun:
Text Understanding from Scratch. CoRR abs/1502.01710 (2015) - [i31]Joan Bruna, Soumith Chintala, Yann LeCun, Serkan Piantino, Arthur Szlam, Mark Tygert:
A theoretical argument for complex-valued convolutional networks. CoRR abs/1503.03438 (2015) - [i30]Junbo Jake Zhao, Michaël Mathieu, Ross Goroshin, Yann LeCun:
Stacked What-Where Auto-encoders. CoRR abs/1506.02351 (2015) - [i29]Ross Goroshin, Michaël Mathieu, Yann LeCun:
Learning to Linearize Under Uncertainty. CoRR abs/1506.03011 (2015) - [i28]Mikael Henaff, Joan Bruna, Yann LeCun:
Deep Convolutional Networks on Graph-Structured Data. CoRR abs/1506.05163 (2015) - [i27]Xiang Zhang, Junbo Jake Zhao, Yann LeCun:
Character-level Convolutional Networks for Text Classification. CoRR abs/1509.01626 (2015) - [i26]Peter Dugan, John Zollweg, Marian Popescu, Denise Risch, Hervé Glotin, Yann LeCun, Christopher W. Clark:
High Performance Computer Acoustic Data Accelerator: A New System for Exploring Marine Mammal Acoustics for Big Data Applications. CoRR abs/1509.03591 (2015) - [i25]Tom Sercu, Christian Puhrsch, Brian Kingsbury, Yann LeCun:
Very Deep Multilingual Convolutional Neural Networks for LVCSR. CoRR abs/1509.08967 (2015) - [i24]Jure Zbontar, Yann LeCun:
Stereo Matching by Training a Convolutional Neural Network to Compare Image Patches. CoRR abs/1510.05970 (2015) - [i23]Xiang Zhang, Yann LeCun:
Universum Prescription: Regularization using Unlabeled Data. CoRR abs/1511.03719 (2015) - [i22]Anna Choromanska, Krzysztof Choromanski, Mariusz Bojarski, Tony Jebara, Sanjiv Kumar, Yann LeCun:
Binary embeddings with structured hashed projections. CoRR abs/1511.05212 (2015) - [i21]Levent Sagun, Thomas Trogdon, Yann LeCun:
Universality in halting time and its applications in optimization. CoRR abs/1511.06444 (2015) - 2014
- [j32]Camille Couprie, Clément Farabet, Laurent Najman, Yann LeCun:
Convolutional nets and watershed cuts for real-time semantic Labeling of RGBD videos. J. Mach. Learn. Res. 15(1): 3489-3511 (2014) - [j31]Jonathan Tompson, Murphy Stein, Yann LeCun, Ken Perlin:
Real-Time Continuous Pose Recovery of Human Hands Using Convolutional Networks. ACM Trans. Graph. 33(5): 169:1-169:10 (2014) - [c108]Arjun Jain, Jonathan Tompson, Yann LeCun, Christoph Bregler:
MoDeep: A Deep Learning Framework Using Motion Features for Human Pose Estimation. ACCV (2) 2014: 302-315 - [c107]Joan Bruna Estrach, Arthur Szlam, Yann LeCun:
Signal recovery from Pooling Representations. ICML 2014: 307-315 - [c106]Emily L. Denton, Wojciech Zaremba, Joan Bruna, Yann LeCun, Rob Fergus:
Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation. NIPS 2014: 1269-1277 - [c105]Jonathan Tompson, Arjun Jain, Yann LeCun, Christoph Bregler:
Joint Training of a Convolutional Network and a Graphical Model for Human Pose Estimation. NIPS 2014: 1799-1807 - [c104]Joan Bruna, Wojciech Zaremba, Arthur Szlam, Yann LeCun:
Spectral Networks and Locally Connected Networks on Graphs. ICLR 2014 - [c103]David Eigen, Jason Tyler Rolfe, Rob Fergus, Yann LeCun:
Understanding Deep Architectures using a Recursive Convolutional Network. ICLR (Workshop Poster) 2014 - [c102]Michaël Mathieu, Mikael Henaff, Yann LeCun:
Fast Training of Convolutional Networks through FFTs. ICLR (Poster) 2014 - [c101]Pierre Sermanet, David Eigen, Xiang Zhang, Michaël Mathieu, Rob Fergus, Yann LeCun:
OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks. ICLR 2014 - [e4]Yoshua Bengio, Yann LeCun:
2nd International Conference on Learning Representations, ICLR 2014, Banff, AB, Canada, April 14-16, 2014, Conference Track Proceedings. 2014 [contents] - [e3]Yoshua Bengio, Yann LeCun:
2nd International Conference on Learning Representations, ICLR 2014, Banff, AB, Canada, April 14-16, 2014, Workshop Track Proceedings. 2014 [contents] - [i20]Emily Denton, Wojciech Zaremba, Joan Bruna, Yann LeCun, Rob Fergus:
Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation. CoRR abs/1404.0736 (2014) - [i19]Michaël Mathieu, Yann LeCun:
Fast Approximation of Rotations and Hessians matrices. CoRR abs/1404.7195 (2014) - [i18]Jonathan Tompson, Arjun Jain, Yann LeCun, Christoph Bregler:
Joint Training of a Convolutional Network and a Graphical Model for Human Pose Estimation. CoRR abs/1406.2984 (2014) - [i17]Jure Zbontar, Yann LeCun:
Computing the Stereo Matching Cost with a Convolutional Neural Network. CoRR abs/1409.4326 (2014) - [i16]Arjun Jain, Jonathan Tompson, Yann LeCun, Christoph Bregler:
MoDeep: A Deep Learning Framework Using Motion Features for Human Pose Estimation. CoRR abs/1409.7963 (2014) - [i15]Mariusz Bojarski, Anna Choromanska, Krzysztof Choromanski, Yann LeCun:
Differentially- and non-differentially-private random decision trees. CoRR abs/1410.6973 (2014) - [i14]Jonathan Tompson, Ross Goroshin, Arjun Jain, Yann LeCun, Christoph Bregler:
Efficient Object Localization Using Convolutional Networks. CoRR abs/1411.4280 (2014) - [i13]Anna Choromanska, Mikael Henaff, Michaël Mathieu, Gérard Ben Arous, Yann LeCun:
The Loss Surface of Multilayer Networks. CoRR abs/1412.0233 (2014) - [i12]Ross Goroshin, Joan Bruna, Jonathan Tompson, David Eigen, Yann LeCun:
Unsupervised Learning of Spatiotemporally Coherent Metrics. CoRR abs/1412.6056 (2014) - 2013
- [j30]Eric J. Humphrey, Juan Pablo Bello, Yann LeCun:
Feature learning and deep architectures: new directions for music informatics. J. Intell. Inf. Syst. 41(3): 461-481 (2013) - [j29]Clément Farabet, Camille Couprie, Laurent Najman, Yann LeCun:
Learning Hierarchical Features for Scene Labeling. IEEE Trans. Pattern Anal. Mach. Intell. 35(8): 1915-1929 (2013) - [c100]Marc Pickett, Benjamin Kuipers, Yann LeCun, Clayton T. Morrison:
Preface. AAAI Workshop: Learning Rich Representations from Low-Level Sensors 2013 - [c99]Pierre Sermanet, Koray Kavukcuoglu, Soumith Chintala, Yann LeCun:
Pedestrian Detection with Unsupervised Multi-stage Feature Learning. CVPR 2013: 3626-3633 - [c98]Camille Couprie, Clément Farabet, Yann LeCun, Laurent Najman:
Causal graph-based video segmentation. ICIP 2013: 4249-4253 - [c97]Tom Schaul, Sixin Zhang, Yann LeCun:
No more pesky learning rates. ICML (3) 2013: 343-351 - [c96]Li Wan, Matthew D. Zeiler, Sixin Zhang, Yann LeCun, Rob Fergus:
Regularization of Neural Networks using DropConnect. ICML (3) 2013: 1058-1066 - [c95]Tommi Vatanen, Tapani Raiko, Harri Valpola, Yann LeCun:
Pushing Stochastic Gradient towards Second-Order Methods - Backpropagation Learning with Transformations in Nonlinearities. ICONIP (1) 2013: 442-449 - [c94]Tommi Vatanen, Tapani Raiko, Harri Valpola, Yann LeCun:
Pushing Stochastic Gradient towards Second-Order Methods -- Backpropagation Learning with Transformations in Nonlinearities. ICLR (Workshop Poster) 2013 - [c93]Joan Bruna, Arthur Szlam, Yann LeCun:
Learning Stable Group Invariant Representations with Convolutional Networks. ICLR (Workshop Poster) 2013 - [c92]Camille Couprie, Clément Farabet, Laurent Najman, Yann LeCun:
Indoor Semantic Segmentation using depth information. ICLR 2013 - [c91]Rostislav Goroshin, Yann LeCun:
Saturating Auto-Encoder. ICLR (Poster) 2013 - [c90]Tom Schaul, Yann LeCun:
Adaptive learning rates and parallelization for stochastic, sparse, non-smooth gradients. ICLR (Poster) 2013 - [c89]Jason Tyler Rolfe, Yann LeCun:
Discriminative Recurrent Sparse Auto-Encoders. ICLR 2013 - [e2]Yoshua Bengio, Yann LeCun:
1st International Conference on Learning Representations, ICLR 2013, Scottsdale, Arizona, USA, May 2-4, 2013, Conference Track Proceedings. 2013 [contents] - [e1]Yoshua Bengio, Yann LeCun:
1st International Conference on Learning Representations, ICLR 2013, Scottsdale, Arizona, USA, May 2-4, 2013, Workshop Track Proceedings. 2013 [contents] - [i11]Camille Couprie, Clément Farabet, Yann LeCun:
Causal graph-based video segmentation. CoRR abs/1301.1671 (2013) - 2012
- [c88]Arthur Szlam, Karol Gregor, Yann LeCun:
Fast Approximations to Structured Sparse Coding and Applications to Object Classification. ECCV (5) 2012: 200-213 - [c87]José M. Álvarez, Theo Gevers, Yann LeCun, Antonio M. López:
Road Scene Segmentation from a Single Image. ECCV (7) 2012: 376-389 - [c86]Yann LeCun:
Learning Invariant Feature Hierarchies. ECCV Workshops (1) 2012: 496-505 - [c85]José M. Álvarez, Yann LeCun, Theo Gevers, Antonio M. López:
Semantic Road Segmentation via Multi-scale Ensembles of Learned Features. ECCV Workshops (2) 2012: 586-595 - [c84]Clément Farabet, Camille Couprie, Laurent Najman, Yann LeCun:
Scene parsing with Multiscale Feature Learning, Purity Trees, and Optimal Covers. ICML 2012 - [c83]Pierre Sermanet, Soumith Chintala, Yann LeCun:
Convolutional neural networks applied to house numbers digit classification. ICPR 2012: 3288-3291 - [c82]Eric J. Humphrey, Juan Pablo Bello, Yann LeCun:
Moving Beyond Feature Design: Deep Architectures and Automatic Feature Learning in Music Informatics. ISMIR 2012: 403-408 - [c81]Phi-Hung Pham, Darko Jelaca, Clément Farabet, Berin Martini, Yann LeCun, Eugenio Culurciello:
NeuFlow: Dataflow vision processing system-on-a-chip. MWSCAS 2012: 1044-1047 - [c80]Tapani Raiko, Harri Valpola, Yann LeCun:
Deep Learning Made Easier by Linear Transformations in Perceptrons. AISTATS 2012: 924-932 - [p4]Yann LeCun, Léon Bottou, Genevieve B. Orr, Klaus-Robert Müller:
Efficient BackProp. Neural Networks: Tricks of the Trade (2nd ed.) 2012: 9-48 - [p3]Patrice Y. Simard, Yann LeCun, John S. Denker, Bernard Victorri:
Transformation Invariance in Pattern Recognition - Tangent Distance and Tangent Propagation. Neural Networks: Tricks of the Trade (2nd ed.) 2012: 235-269 - [i10]Clément Farabet, Camille Couprie, Laurent Najman, Yann LeCun:
Scene Parsing with Multiscale Feature Learning, Purity Trees, and Optimal Covers. CoRR abs/1202.2160 (2012) - [i9]Arthur Szlam, Karol Gregor, Yann LeCun:
Fast approximations to structured sparse coding and applications to object classification. CoRR abs/1202.6384 (2012) - [i8]Pierre Sermanet, Soumith Chintala, Yann LeCun:
Convolutional Neural Networks Applied to House Numbers Digit Classification. CoRR abs/1204.3968 (2012) - [i7]Tom Schaul, Sixin Zhang, Yann LeCun:
No More Pesky Learning Rates. CoRR abs/1206.1106 (2012) - [i6]Pierre Sermanet, Koray Kavukcuoglu, Soumith Chintala, Yann LeCun:
Pedestrian Detection with Unsupervised Multi-Stage Feature Learning. CoRR abs/1212.0142 (2012) - 2011
- [j28]Juan Pablo Bello, Yann LeCun, Robert Rowe:
Concerto for violin and Markov model: technical perspective. Commun. ACM 54(3): 86 (2011) - [c79]Polina Akselrod, Faye Zhao, Ifigeneia Derekli, Clément Farabet, Berin Martini, Yann LeCun, Eugenio Culurciello:
Hardware accelerated visual attention algorithm. CISS 2011: 1-6 - [c78]Clément Farabet, Berin Martini, B. Corda, Polina Akselrod, Eugenio Culurciello, Yann LeCun:
NeuFlow: A runtime reconfigurable dataflow processor for vision. CVPR Workshops 2011: 109-116 - [c77]Y-Lan Boureau, Nicolas Le Roux, Francis R. Bach, Jean Ponce, Yann LeCun:
Ask the locals: Multi-way local pooling for image recognition. ICCV 2011: 2651-2658 - [c76]Pierre Sermanet, Yann LeCun:
Traffic sign recognition with multi-scale Convolutional Networks. IJCNN 2011: 2809-2813 - [c75]Mikael Henaff, Kevin Jarrett, Koray Kavukcuoglu, Yann LeCun:
Unsupervised Learning of Sparse Features for Scalable Audio Classification. ISMIR 2011: 681-686 - [c74]Arthur Szlam, Karol Gregor, Yann LeCun:
Structured sparse coding via lateral inhibition. NIPS 2011: 1116-1124 - [i5]Karol Gregor, Yann LeCun:
Efficient Learning of Sparse Invariant Representations. CoRR abs/1105.5307 (2011) - [i4]Karol Gregor, Yann LeCun:
Learning Representations by Maximizing Compression. CoRR abs/1108.1169 (2011) - 2010
- [c73]Y-Lan Boureau, Francis R. Bach, Yann LeCun, Jean Ponce:
Learning mid-level features for recognition. CVPR 2010: 2559-2566 - [c72]Graham W. Taylor, Rob Fergus, Yann LeCun, Christoph Bregler:
Convolutional Learning of Spatio-temporal Features. ECCV (6) 2010: 140-153 - [c71]Y-Lan Boureau, Jean Ponce, Yann LeCun:
A Theoretical Analysis of Feature Pooling in Visual Recognition. ICML 2010: 111-118 - [c70]Karol Gregor, Yann LeCun:
Learning Fast Approximations of Sparse Coding. ICML 2010: 399-406 - [c69]Matthew Koichi Grimes, Dragomir Anguelov, Yann LeCun:
Hybrid hessians for flexible optimization of pose graphs. IROS 2010: 2997-3004 - [c68]Yann LeCun, Koray Kavukcuoglu, Clément Farabet:
Convolutional networks and applications in vision. ISCAS 2010: 253-256 - [c67]Clément Farabet, Berin Martini, Polina Akselrod, Selçuk Talay, Yann LeCun, Eugenio Culurciello:
Hardware accelerated convolutional neural networks for synthetic vision systems. ISCAS 2010: 257-260 - [c66]Koray Kavukcuoglu, Pierre Sermanet, Y-Lan Boureau, Karol Gregor, Michaël Mathieu, Yann LeCun:
Learning Convolutional Feature Hierarchies for Visual Recognition. NIPS 2010: 1090-1098 - [c65]Diederik P. Kingma, Yann LeCun:
Regularized estimation of image statistics by Score Matching. NIPS 2010: 1126-1134 - [i3]Karol Gregor, Yann LeCun:
Emergence of Complex-Like Cells in a Temporal Product Network with Local Receptive Fields. CoRR abs/1006.0448 (2010) - [i2]Arthur Szlam, Koray Kavukcuoglu, Yann LeCun:
Convolutional Matching Pursuit and Dictionary Training. CoRR abs/1010.0422 (2010) - [i1]Koray Kavukcuoglu, Marc'Aurelio Ranzato, Yann LeCun:
Fast Inference in Sparse Coding Algorithms with Applications to Object Recognition. CoRR abs/1010.3467 (2010)
2000 – 2009
- 2009
- [j27]Pierre Sermanet, Raia Hadsell, Marco Scoffier, Matthew Grimes, Jan Ben, Ayse Erkan, Chris Crudele, Urs Miller, Yann LeCun:
A multirange architecture for collision-free off-road robot navigation. J. Field Robotics 26(1): 52-87 (2009) - [j26]Raia Hadsell, Pierre Sermanet, Jan Ben, Ayse Erkan, Marco Scoffier, Koray Kavukcuoglu, Urs Muller, Yann LeCun:
Learning long-range vision for autonomous off-road driving. J. Field Robotics 26(2): 120-144 (2009) - [c64]Koray Kavukcuoglu, Marc'Aurelio Ranzato, Rob Fergus, Yann LeCun:
Learning invariant features through topographic filter maps. CVPR 2009: 1605-1612 - [c63]Clément Farabet, Cyril Poulet, Jefferson Y. Han, Yann LeCun:
CNP: An FPGA-based processor for Convolutional Networks. FPL 2009: 32-37 - [c62]Kevin Jarrett, Koray Kavukcuoglu, Marc'Aurelio Ranzato, Yann LeCun:
What is the best multi-stage architecture for object recognition? ICCV 2009: 2146-2153 - [c61]Clément Farabet, Cyril Poulet, Yann LeCun:
An FPGA-based stream processor for embedded real-time vision with Convolutional Networks. ICCV Workshops 2009: 878-885 - [c60]Kai Yu, Ruslan Salakhutdinov, Yann LeCun, Geoffrey E. Hinton, Yoshua Bengio:
Workshop summary: Workshop on learning feature hierarchies. ICML 2009: 5 - [c59]Matthew Grimes, Yann LeCun:
Efficient off-road localization using visually corrected odometry. ICRA 2009: 2649-2654 - [c58]Pierre Sermanet, Koray Kavukcuoglu, Yann LeCun:
EBLearn: Open-Source Energy-Based Learning in C++. ICTAI 2009: 693-697 - [c57]Piotr Mirowski, Yann LeCun:
Dynamic Factor Graphs for Time Series Modeling. ECML/PKDD (2) 2009: 128-143 - 2008
- [j25]Andrew W. Fitzgibbon, Camillo J. Taylor, Yann LeCun:
Editorial. Int. J. Comput. Vis. 80(1): 1-2 (2008) - [c56]Raia Hadsell, Ayse Erkan, Pierre Sermanet, Marco Scoffier, Urs Muller, Yann LeCun:
Deep belief net learning in a long-range vision system for autonomous off-road driving. IROS 2008: 628-633 - [c55]Pierre Sermanet, Raia Hadsell, Marco Scoffier, Urs Muller, Yann LeCun:
Mapping and planning under uncertainty in mobile robots with long-range perception. IROS 2008: 2525-2530 - 2007
- [j24]Margarita Osadchy, Yann LeCun, Matthew L. Miller:
Synergistic Face Detection and Pose Estimation with Energy-Based Models. J. Mach. Learn. Res. 8: 1197-1215 (2007) - [j23]Sören Sonnenburg, Mikio L. Braun, Cheng Soon Ong, Samy Bengio, Léon Bottou, Geoffrey Holmes, Yann LeCun, Klaus-Robert Müller, Fernando Pereira, Carl Edward Rasmussen, Gunnar Rätsch, Bernhard Schölkopf, Alexander J. Smola, Pascal Vincent, Jason Weston, Robert C. Williamson:
The Need for Open Source Software in Machine Learning. J. Mach. Learn. Res. 8: 2443-2466 (2007) - [j22]Marc'Aurelio Ranzato, P. E. Taylor, James M. House, R. C. Flagan, Yann LeCun, Pietro Perona:
Automatic recognition of biological particles in microscopic images. Pattern Recognit. Lett. 28(1): 31-39 (2007) - [c54]Piotr W. Mirowski, Deepak Madhavan, Yann LeCun:
Time-Delay Neural Networks and Independent Component Analysis for EEG-Based Prediction of Epileptic Seizures Propagation. AAAI 2007: 1892-1893 - [c53]Marc'Aurelio Ranzato, Fu Jie Huang, Y-Lan Boureau, Yann LeCun:
Unsupervised Learning of Invariant Feature Hierarchies with Applications to Object Recognition. CVPR 2007 - [c52]Yann LeCun, Sumit Chopra, Marc'Aurelio Ranzato, Fu Jie Huang:
Energy-Based Models in Document Recognition and Computer Vision. ICDAR 2007: 337-341 - [c51]Marc'Aurelio Ranzato, Yann LeCun:
A Sparse and Locally Shift Invariant Feature Extractor Applied to Document Images. ICDAR 2007: 1213-1217 - [c50]Ayse Erkan, Raia Hadsell, Pierre Sermanet, Jan Ben, Urs Muller, Yann LeCun:
Adaptive long range vision in unstructured terrain. IROS 2007: 2421-2426 - [c49]Sumit Chopra, Trivikraman Thampy, John Leahy, Andrew Caplin, Yann LeCun:
Discovering the hidden structure of house prices with a non-parametric latent manifold model. KDD 2007: 173-182 - [c48]Marc'Aurelio Ranzato, Y-Lan Boureau, Yann LeCun:
Sparse Feature Learning for Deep Belief Networks. NIPS 2007: 1185-1192 - [c47]Raia Hadsell, Pierre Sermanet, Jan Ben, Ayse Erkan, Jeff Han, Urs Muller, Yann LeCun:
Online Learning for Offroad Robots: Spatial Label Propagation to Learn Long-Range Traversability. Robotics: Science and Systems 2007 - [c46]Marc'Aurelio Ranzato, Y-Lan Boureau, Sumit Chopra, Yann LeCun:
A Unified Energy-Based Framework for Unsupervised Learning. AISTATS 2007: 371-379 - 2006
- [c45]Margarita Osadchy, Yann LeCun, Matthew L. Miller:
Synergistic Face Detection and Pose Estimation with Energy-Based Models. Toward Category-Level Object Recognition 2006: 196-206 - [c44]Fu Jie Huang, Yann LeCun:
Large-scale Learning with SVM and Convolutional for Generic Object Categorization. CVPR (1) 2006: 284-291 - [c43]Raia Hadsell, Sumit Chopra, Yann LeCun:
Dimensionality Reduction by Learning an Invariant Mapping. CVPR (2) 2006: 1735-1742 - [c42]Marc'Aurelio Ranzato, Christopher S. Poultney, Sumit Chopra, Yann LeCun:
Efficient Learning of Sparse Representations with an Energy-Based Model. NIPS 2006: 1137-1144 - 2005
- [j21]F. Ning, D. Delhomme, Yann LeCun, F. Piano, Léon Bottou, Paolo Emilio Barbano:
Toward Automatic Phenotyping of Developing Embryos From Videos. IEEE Trans. Image Process. 14(9): 1360-1371 (2005) - [c41]Yann LeCun, Fu Jie Huang:
Loss Functions for Discriminative Training of Energy-Based Models. AISTATS 2005: 206-213 - [c40]Sumit Chopra, Raia Hadsell, Yann LeCun:
Learning a Similarity Metric Discriminatively, with Application to Face Verification. CVPR (1) 2005: 539-546 - [c39]Yann LeCun, Urs Muller, Jan Ben, Eric Cosatto, Beat Flepp:
Off-Road Obstacle Avoidance through End-to-End Learning. NIPS 2005: 739-746 - 2004
- [c38]Yann LeCun, Fu Jie Huang, Léon Bottou:
Learning Methods for Generic Object Recognition with Invariance to Pose and Lighting. CVPR (2) 2004: 97-104 - [c37]Margarita Osadchy, Matthew L. Miller, Yann LeCun:
Synergistic Face Detection and Pose Estimation with Energy-Based Models. NIPS 2004: 1017-1024 - 2003
- [c36]Léon Bottou, Yann LeCun:
Large Scale Online Learning. NIPS 2003: 217-224 - 2002
- [c35]Lawrence K. Saul, Daniel D. Lee, Charles L. Isbell Jr., Yann LeCun:
Real Time Voice Processing with Audiovisual Feedback: Toward Autonomous Agents with Perfect Pitch. NIPS 2002: 1181-1188 - 2001
- [c34]Léon Bottou, Patrick Haffner, Yann LeCun:
Efficient Conversion of Digital Documents to Multilayer Raster Formats. ICDAR 2001: 444-449 - 2000
- [j20]Patrice Y. Simard, Yann LeCun, John S. Denker, Bernard Victorri:
Transformation invariance in pattern recognition: Tangent distance and propagation. Int. J. Imaging Syst. Technol. 11(3): 181-197 (2000)
1990 – 1999
- 1999
- [c33]Patrick Haffner, Léon Bottou, Paul G. Howard, Yann LeCun:
DjVu: Analyzing and Compressing Scanned Documents for Internet Distribution. ICDAR 1999: 625-628 - [c32]Patrick Haffner, Yann LeCun, Léon Bottou, Paul G. Howard, Pascal Vincent, Bill Riemers:
Color Documents on the Web with DJVU. ICIP (1) 1999: 239-243 - [c31]Yann LeCun, Patrick Haffner, Léon Bottou, Yoshua Bengio:
Object Recognition with Gradient-Based Learning. Shape, Contour and Grouping in Computer Vision 1999: 319- - 1998
- [j19]Léon Bottou, Patrick Haffner, Paul G. Howard, Patrice Y. Simard, Yoshua Bengio, Yann LeCun:
High quality document image compression with "DjVu". J. Electronic Imaging 7(3): 410-425 (1998) - [j18]Richard V. Cox, Barry G. Haskell, Yann LeCun, Behzad Shahraray, Lawrence R. Rabiner:
On the applications of multimedia processing to communications. Proc. IEEE 86(5): 755-824 (1998) - [j17]Yann LeCun, Léon Bottou, Yoshua Bengio, Patrick Haffner:
Gradient-based learning applied to document recognition. Proc. IEEE 86(11): 2278-2324 (1998) - [j16]Barry G. Haskell, Paul G. Howard, Yann LeCun, Atul Puri, Jörn Ostermann, M. Reha Civanlar, Lawrence R. Rabiner, Léon Bottou, Patrick Haffner:
Image and video coding-emerging standards and beyond. IEEE Trans. Circuits Syst. Video Technol. 8(7): 814-837 (1998) - [j15]Rama Chellappa, Kunihiko Fukushima, Aggelos K. Katsaggelos, Sun-Yuan Kung, Yann LeCun, Nasser M. Nasrabadi, Tomaso A. Poggio:
Guest Editorial Applications Of Artificial Neural Networks To Image Processing. IEEE Trans. Image Process. 7(8): 1093-1096 (1998) - [c30]Patrick Haffner, Léon Bottou, Paul G. Howard, Patrice Y. Simard, Yoshua Bengio, Yann LeCun:
Browsing through High Quality Document Images with DjVu. ADL 1998: 309-318 - [c29]Yann LeCun, Léon Bottou, Patrick Haffner, Paul G. Howard:
DjVu: a Compression Method for Distributing Scanned Documents in Color over the Internet. CIC 1998: 220-223 - [c28]Patrice Y. Simard, Léon Bottou, Patrick Haffner, Yann LeCun:
Boxlets: A Fast Convolution Algorithm for Signal Processing and Neural Networks. NIPS 1998: 571-577 - 1997
- [c27]Léon Bottou, Yoshua Bengio, Yann LeCun:
Global Training of Document Processing Systems Using Graph Transformer Networks. CVPR 1997: 489-494 - [c26]Yann LeCun, Léon Bottou, Yoshua Bengio:
Reading checks with multilayer graph transformer networks. ICASSP 1997: 151-154 - [c25]Richard V. Cox, Barry G. Haskell, Yann LeCun, Behzad Shahraray, Lawrence R. Rabiner:
On the Applications of Multimedia Processing to Telecommunications. ICIP (1) 1997: 5-8 - [c24]Mazin Rahim, Yoshua Bengio, Yann LeCun:
Discriminative feature and model design for automatic speech recognition. EUROSPEECH 1997: 75-78 - 1996
- [p2]Yann LeCun, Léon Bottou, Genevieve B. Orr, Klaus-Robert Müller:
Effiicient BackProp. Neural Networks: Tricks of the Trade 1996: 9-50 - [p1]Patrice Y. Simard, Yann LeCun, John S. Denker, Bernard Victorri:
Transformation Invariance in Pattern Recognition-Tangent Distance and Tangent Propagation. Neural Networks: Tricks of the Trade 1996: 239-27 - 1995
- [j14]Yoshua Bengio, Yann LeCun, Craig R. Nohl, Christopher J. C. Burges:
LeRec: a NN/HMM hybrid for on-line handwriting recognition. Neural Comput. 7(6): 1289-1303 (1995) - 1994
- [j13]Vladimir Vapnik, Esther Levin, Yann LeCun:
Measuring the VC-Dimension of a Learning Machine. Neural Comput. 6(5): 851-876 (1994) - [j12]Harris Drucker, Corinna Cortes, Lawrence D. Jackel, Yann LeCun, Vladimir Vapnik:
Boosting and Other Ensemble Methods. Neural Comput. 6(6): 1289-1301 (1994) - [c23]Harris Drucker, Corinna Cortes, Lawrence D. Jackel, Yann LeCun, Vladimir Vapnik:
Boosting and Other Machine Learning Algorithms. ICML 1994: 53-61 - [c22]Léon Bottou, Corinna Cortes, John S. Denker, Harris Drucker, Isabelle Guyon, Larry D. Jackel, Yann LeCun, Urs A. Müller, Eduard Säckinger, Patrice Y. Simard, Vladimir Vapnik:
Comparison of classifier methods: a case study in handwritten digit recognition. ICPR (2) 1994: 77-82 - [c21]Yann LeCun, Yoshua Bengio:
Word-level training of a handwritten word recognizer based on convolutional neural networks. ICPR (2) 1994: 88-92 - [c20]Patrice Y. Simard, Yann LeCun, John S. Denker:
Memory-based character recognition using a transformation invariant metric. ICPR (2) 1994: 262-267 - [c19]Yoshua Bengio, Yann LeCun:
Word normalization for online handwritten word recognition. ICPR (2) 1994: 409-413 - 1993
- [j11]Jane Bromley, James W. Bentz, Léon Bottou, Isabelle Guyon, Yann LeCun, Cliff Moore, Eduard Säckinger, Roopak Shah:
Signature Verification Using A "Siamese" Time Delay Neural Network. Int. J. Pattern Recognit. Artif. Intell. 7(4): 669-688 (1993) - [j10]Christopher J. C. Burges, Jan Ben, John S. Denker, Yann LeCun, Craig R. Nohl:
Off Line Recognition of Handwritten Postal Words Using Neural Networks. Int. J. Pattern Recognit. Artif. Intell. 7(4): 689-704 (1993) - [c18]Quen-Zong Wu, Yann LeCun, Lawrence D. Jackel, Bor-Shenn Jeng:
On-line recognition of limited-vocabulary Chinese character using multiple convolutional neural networks. ISCAS 1993: 2435-2438 - [c17]Jane Bromley, Isabelle Guyon, Yann LeCun, Eduard Säckinger, Roopak Shah:
Signature Verification Using a Siamese Time Delay Neural Network. NIPS 1993: 737-744 - [c16]Yoshua Bengio, Yann LeCun, Donnie Henderson:
Globally Trained Handwritten Word Recognizer Using Spatial Representation, Convolutional Neural Networks, and Hidden Markov Models. NIPS 1993: 937-944 - 1992
- [j9]Ofer Matan, Henry S. Baird, Jane Bromley, Christopher J. C. Burges, John S. Denker, Lawrence D. Jackel, Yann LeCun, Edwin P. D. Pednault, William Satterfield, Charles E. Stenard, Timothy J. Thompson:
Reading Handwritten Digits: A ZIP Code Recognition System. Computer 25(7): 59-63 (1992) - [j8]Bernhard E. Boser, Eduard Säckinger, Jane Bromley, Yann LeCun, Lawrence D. Jackel:
Hardware requirements for neural network pattern classifiers: a case study and implementation. IEEE Micro 12(1): 32-40 (1992) - [j7]Eduard Säckinger, Bernhard E. Boser, Jane Bromley, Yann LeCun, Lawrence D. Jackel:
Application of the ANNA neural network chip to high-speed character recognition. IEEE Trans. Neural Networks 3(3): 498-505 (1992) - [j6]Harris Drucker, Yann LeCun:
Improving generalization performance using double backpropagation. IEEE Trans. Neural Networks 3(6): 991-997 (1992) - [c15]Patrice Y. Simard, Yann LeCun, John S. Denker, Bernard Victorri:
An efficient algorithm for learning invariance in adaptive classifiers. ICPR (2) 1992: 651-655 - [c14]Patrice Y. Simard, Yann LeCun, John S. Denker:
Efficient Pattern Recognition Using a New Transformation Distance. NIPS 1992: 50-58 - [c13]Yann LeCun, Patrice Y. Simard, Barak A. Pearlmutter:
Automatic Learning Rate Maximization in Large Adaptive Machines. NIPS 1992: 156-163 - 1991
- [j5]Bernhard E. Boser, Eduard Sackinger, Jane Bromley, Yann LeCun, Lawrence D. Jackel:
An analog neural network processor with programmable topology. IEEE J. Solid State Circuits 26(12): 2017-2025 (1991) - [j4]Isabelle Guyon, P. Albrecht, Yann LeCun, John S. Denker, Wayne E. Hubbard:
Design of a neural network character recognizer for a touch terminal. Pattern Recognit. 24(2): 105-119 (1991) - [c12]Lawrence D. Jackel, Charles E. Stenard, Henry S. Baird, Bernhard E. Boser, Jane Bromley, Christopher J. C. Burges, John S. Denker, Hans Peter Graf, Donnie Henderson, Richard E. Howard, Wayne E. Hubbard, Yann LeCun, Ofer Matan, Edwin P. D. Pednault, William Satterfield, Eduard Säckinger, Timothy J. Thompson:
A neural network approach to handprint character recognition. Compcon 1991: 472-475 - [c11]Ofer Matan, Christopher J. C. Burges, Yann LeCun, John S. Denker:
Multi-Digit Recognition Using a Space Displacement Neural Network. NIPS 1991: 488-495 - [c10]Patrice Y. Simard, Yann LeCun:
Reverse TDNN: An Architecture For Trajectory Generation. NIPS 1991: 579-588 - [c9]Patrice Y. Simard, Bernard Victorri, Yann LeCun, John S. Denker:
Tangent Prop - A Formalism for Specifying Selected Invariances in an Adaptive Network. NIPS 1991: 895-903 - 1990
- [c8]Yann LeCun, Ofer Matan, Bernhard E. Boser, John S. Denker, Don Henderson, Richard E. Howard, Wayne E. Hubbard, L. D. Jacket, Henry S. Baird:
Handwritten zip code recognition with multilayer networks. ICPR (2) 1990: 35-40 - [c7]Lawrence D. Jackel, Bernhard E. Boser, John S. Denker, Hans Peter Graf, Yann LeCun, Isabelle Guyon, Donnie Henderson, Richard E. Howard, Wayne E. Hubbard, Sara A. Solla:
Hardware requirements for neural-net optical character recognition. IJCNN 1990: 855-861 - [c6]John S. Denker, Yann LeCun:
Transforming Neural-Net Output Levels to Probability Distributions. NIPS 1990: 853-859 - [c5]Yann LeCun, Ido Kanter, Sara A. Solla:
Second Order Properties of Error Surfaces. NIPS 1990: 918-924
1980 – 1989
- 1989
- [j3]Yann LeCun, Lawrence D. Jackel, Bernhard E. Boser, John S. Denker, Hans Peter Graf, Isabelle Guyon, Don Henderson, Richard E. Howard, Wayne E. Hubbard:
Handwritten digit recognition: applications of neural network chips and automatic learning. IEEE Commun. Mag. 27(11): 41-46 (1989) - [j2]Yann LeCun, Bernhard E. Boser, John S. Denker, Donnie Henderson, Richard E. Howard, Wayne E. Hubbard, Lawrence D. Jackel:
Backpropagation Applied to Handwritten Zip Code Recognition. Neural Comput. 1(4): 541-551 (1989) - [c4]Yann LeCun, Larry D. Jackel, Bernhard E. Boser, John S. Denker, Hans Peter Graf, Isabelle Guyon, Donnie Henderson, Richard E. Howard, Wayne E. Hubbard:
Handwritten Digit Recognition: Applications of Neural Net Chips and Automatic Learning. NATO Neurocomputing 1989: 303-318 - [c3]Yann LeCun, Bernhard E. Boser, John S. Denker, Donnie Henderson, Richard E. Howard, Wayne E. Hubbard, Lawrence D. Jackel:
Handwritten Digit Recognition with a Back-Propagation Network. NIPS 1989: 396-404 - [c2]Yann LeCun, John S. Denker, Sara A. Solla:
Optimal Brain Damage. NIPS 1989: 598-605 - 1988
- [j1]Yann LeCun:
Using curvature information to improve back-propagation. Neural Networks 1(Supplement-1): 168-171 (1988) - [c1]Yann LeCun, Conrad C. Galland, Geoffrey E. Hinton:
GEMINI: Gradient Estimation Through Matrix Inversion After Noise Injection. NIPS 1988: 141-148
Coauthor Index
Mido Assran
aka: Mahmoud Assran
aka: Mahmoud Assran
Joan Bruna
aka: Joan Bruna Estrach
aka: Joan Bruna Estrach
Lawrence D. Jackel
aka: Larry D. Jackel
aka: Larry D. Jackel
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2026-04-17 00:23 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
