LeCun, Yann

175 publications

ICLR 2025 $\mathbb{X}$-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs Vlad Sobal, Mark Ibrahim, Randall Balestriero, Vivien Cabannes, Diane Bouchacourt, Pietro Astolfi, Kyunghyun Cho, Yann LeCun
ICML 2025 DINO-WM: World Models on Pre-Trained Visual Features Enable Zero-Shot Planning Gaoyue Zhou, Hengkai Pan, Yann Lecun, Lerrel Pinto
ICLR 2025 Hierarchical World Models as Visual Whole-Body Humanoid Controllers Nicklas Hansen, S V Jyothir, Vlad Sobal, Yann LeCun, Xiaolong Wang, Hao Su
AISTATS 2025 Improving Pre-Trained Self-Supervised Embeddings Through Effective Entropy Maximization Deep Chakraborty, Yann LeCun, Tim G. J. Rudner, Erik Learned-Miller
ICML 2025 Layer by Layer: Uncovering Hidden Representations in Language Models Oscar Skean, Md Rifat Arefin, Dan Zhao, Niket Nikul Patel, Jalal Naghiyev, Yann Lecun, Ravid Shwartz-Ziv
NeurIPS 2025 Learning from Reward-Free Offline Data: A Case for Planning with Latent Dynamics Models Vlad Sobal, Wancong Zhang, Kyunghyun Cho, Randall Balestriero, Tim G. J. Rudner, Yann LeCun
ICLR 2025 LiveBench: A Challenging, Contamination-Limited LLM Benchmark 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 Venkat Naidu, Chinmay Hegde, Yann LeCun, Tom Goldstein, Willie Neiswanger, Micah Goldblum
ICCV 2025 MetaMorph: Multimodal Understanding and Generation via Instruction Tuning Shengbang Tong, David Fan, Jiachen Li, Yunyang Xiong, Xinlei Chen, Koustuv Sinha, Michael Rabbat, Yann LeCun, Saining Xie, Zhuang Liu
CVPR 2025 Navigation World Models Amir Bar, Gaoyue Zhou, Danny Tran, Trevor Darrell, Yann LeCun
NeurIPS 2025 OSVI-WM: One-Shot Visual Imitation for Unseen Tasks Using World-Model-Guided Trajectory Generation Raktim Gautam Goswami, Prashanth Krishnamurthy, Yann LeCun, Farshad Khorrami
ICLR 2025 PooDLeđŸ©: Pooled and Dense Self-Supervised Learning from Naturalistic Videos Alex N Wang, Christopher Hoang, Yuwen Xiong, Yann LeCun, Mengye Ren
CVPR 2025 Rate-in: Information-Driven Adaptive Dropout Rates for Improved Inference-Time Uncertainty Estimation Tal Zeevi, Ravid Shwartz-Ziv, Yann LeCun, Lawrence H. Staib, John A. Onofrey
CVPR 2025 RoboPEPP: Vision-Based Robot Pose and Joint Angle Estimation Through Embedding Predictive Pre-Training Raktim Gautam Goswami, Prashanth Krishnamurthy, Yann LeCun, Farshad Khorrami
ICCV 2025 Scaling Language-Free Visual Representation Learning David Fan, Shengbang Tong, Jiachen Zhu, Koustuv Sinha, Zhuang Liu, Xinlei Chen, Michael Rabbat, Nicolas Ballas, Yann LeCun, Amir Bar, Saining Xie
ICLR 2025 Seq-VCR: Preventing Collapse in Intermediate Transformer Representations for Enhanced Reasoning Md Rifat Arefin, Gopeshh Subbaraj, Nicolas Gontier, Yann LeCun, Irina Rish, Ravid Shwartz-Ziv, Christopher Pal
ICLRW 2025 Stress-Testing Offline Reward-Free Reinforcement Learning: A Case for Planning with Latent Dynamics Models Vlad Sobal, Wancong Zhang, Kyunghyun Cho, Randall Balestriero, Tim G. J. Rudner, Yann LeCun
CVPR 2025 Transformers Without Normalization Jiachen Zhu, Xinlei Chen, Kaiming He, Yann LeCun, Zhuang Liu
ICLR 2025 URLOST: Unsupervised Representation Learning Without Stationarity or Topology Zeyu Yun, Juexiao Zhang, Yann LeCun, Yubei Chen
NeurIPS 2025 Whole-Body Conditioned Egocentric Video Prediction Yutong Bai, Danny Tran, Amir Bar, Yann LeCun, Trevor Darrell, Jitendra Malik
ICMLW 2024 $\mathbb{X}$-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs Vlad Sobal, Mark Ibrahim, Randall Balestriero, Vivien Cabannes, Diane Bouchacourt, Pietro Astolfi, Kyunghyun Cho, Yann LeCun
NeurIPSW 2024 $\mathbb{X}$-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs Vlad Sobal, Mark Ibrahim, Randall Balestriero, Vivien Cabannes, Diane Bouchacourt, Pietro Astolfi, Kyunghyun Cho, Yann LeCun
TMLR 2024 Blockwise Self-Supervised Learning at Scale Shoaib Siddiqui, David Krueger, Yann LeCun, Stephane Deny
NeurIPS 2024 Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs 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
ECCV 2024 EgoPet: Egomotion and Interaction Data from an Animal's Perspective Amir Bar, Arya Bakhtiar, Danny L Tran, Antonio Loquercio, Jathushan Rajasegaran, Yann Lecun, Amir Globerson, Trevor Darrell
CVPR 2024 Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs Shengbang Tong, Zhuang Liu, Yuexiang Zhai, Yi Ma, Yann LeCun, Saining Xie
NeurIPS 2024 Fine-Tuning Large Vision-Language Models as Decision-Making Agents via Reinforcement Learning Yuexiang Zhai, Hao Bai, Zipeng Lin, Jiayi Pan, Shengbang Tong, Yifei Zhou, Alane Suhr, Saining Xie, Yann LeCun, Yi Ma, Sergey Levine
NeurIPS 2024 G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering Xiaoxin He, Yijun Tian, Yifei Sun, Nitesh V. Chawla, Thomas Laurent, Yann LeCun, Xavier Bresson, Bryan Hooi
ICLR 2024 GAIA: A Benchmark for General AI Assistants Grégoire Mialon, Clémentine Fourrier, Thomas Wolf, Yann LeCun, Thomas Scialom
ICLR 2024 Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning Xiaoxin He, Xavier Bresson, Thomas Laurent, Adam Perold, Yann LeCun, Bryan Hooi
ICML 2024 How Learning by Reconstruction Produces Uninformative Features for Perception Randall Balestriero, Yann Lecun
TMLR 2024 Revisiting Feature Prediction for Learning Visual Representations from Video Adrien Bardes, Quentin Garrido, Jean Ponce, Xinlei Chen, Michael Rabbat, Yann LeCun, Mido Assran, Nicolas Ballas
NeurIPSW 2024 Squeezing Performance from Pathology Foundation Models with Chained Hyperparameter Searches Joseph Cappadona, Ken Gary Zeng, Carlos Fernandez-Granda, Jan Witowski, Yann LeCun, Krzysztof J. Geras
ICML 2024 Stochastic Positional Embeddings Improve Masked Image Modeling Amir Bar, Florian Bordes, Assaf Shocher, Mido Assran, Pascal Vincent, Nicolas Ballas, Trevor Darrell, Amir Globerson, Yann Lecun
NeurIPSW 2024 The Birth of Self Supervised Learning: A Supervised Theory Randall Balestriero, Yann LeCun
ICML 2024 The Entropy Enigma: Success and Failure of Entropy Minimization Ori Press, Ravid Shwartz-Ziv, Yann Lecun, Matthias Bethge
ICLRW 2024 Towards an Improved Understanding and Utilization of Maximum Manifold Capacity Representations Rylan Schaeffer, Berivan Isik, Dhruv Bhandarkar Pai, Andres Carranza, Victor Lecomte, Alyssa Unell, Mikail Khona, Thomas Edward Yerxa, Yann LeCun, SueYeon Chung, Andrey Gromov, Ravid Shwartz-Ziv, Sanmi Koyejo
CPAL 2024 Unsupervised Learning of Structured Representation via Closed-Loop Transcription Shengbang Tong, Xili Dai, Yubei Chen, Mingyang Li, Zengyi Li, Brent Yi, Yann LeCun, Yi Ma
ICML 2023 A Generalization of ViT/MLP-Mixer to Graphs Xiaoxin He, Bryan Hooi, Thomas Laurent, Adam Perold, Yann Lecun, Xavier Bresson
ICCV 2023 Active Self-Supervised Learning: A Few Low-Cost Relationships Are All You Need Vivien Cabannes, Leon Bottou, Yann Lecun, Randall Balestriero
CVPRW 2023 Adapting Grounded Visual Question Answering Models to Low Resource Languages Ying Wang, Jonas Pfeiffer, Nicolas Carion, Yann LeCun, Aishwarya Kamath
NeurIPS 2023 An Information Theory Perspective on Variance-Invariance-Covariance Regularization Ravid Shwartz-Ziv, Randall Balestriero, Kenji Kawaguchi, Tim G. J. Rudner, Yann LeCun
NeurIPSW 2023 An Information-Theoretic Understanding of Maximum Manifold Capacity Representations Rylan Schaeffer, Berivan Isik, Victor Lecomte, Mikail Khona, Yann LeCun, Andrey Gromov, Ravid Shwartz-Ziv, Sanmi Koyejo
NeurIPSW 2023 An Information-Theoretic Understanding of Maximum Manifold Capacity Representations Victor Lecomte, Rylan Schaeffer, Berivan Isik, Mikail Khona, Yann LeCun, Sanmi Koyejo, Andrey Gromov, Ravid Shwartz-Ziv
NeurIPSW 2023 An Information-Theoretic Understanding of Maximum Manifold Capacity Representations Berivan Isik, Victor Lecomte, Rylan Schaeffer, Yann LeCun, Mikail Khona, Ravid Shwartz-Ziv, Sanmi Koyejo, Andrey Gromov
TMLR 2023 Augmented Language Models: A Survey Grégoire Mialon, Roberto Dessi, Maria Lomeli, Christoforos Nalmpantis, Ramakanth Pasunuru, Roberta Raileanu, Baptiste Roziere, Timo Schick, Jane Dwivedi-Yu, Asli Celikyilmaz, Edouard Grave, Yann LeCun, Thomas Scialom
TMLR 2023 Bag of Image Patch Embedding Behind the Success of Self-Supervised Learning Yubei Chen, Adrien Bardes, Zengyi Li, Yann LeCun
WACV 2023 Compact and Optimal Deep Learning with Recurrent Parameter Generators Jiayun Wang, Yubei Chen, Stella X. Yu, Brian Cheung, Yann LeCun
ICLR 2023 Minimalistic Unsupervised Representation Learning with the Sparse Manifold Transform Yubei Chen, Zeyu Yun, Yi Ma, Bruno Olshausen, Yann LeCun
ICLR 2023 On the Duality Between Contrastive and Non-Contrastive Self-Supervised Learning Quentin Garrido, Yubei Chen, Adrien Bardes, Laurent Najman, Yann LeCun
ICML 2023 RankMe: Assessing the Downstream Performance of Pretrained Self-Supervised Representations by Their Rank Quentin Garrido, Randall Balestriero, Laurent Najman, Yann Lecun
NeurIPS 2023 Reverse Engineering Self-Supervised Learning Ido Ben-Shaul, Ravid Shwartz-Ziv, Tomer Galanti, Shai Dekel, Yann LeCun
CVPR 2023 Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture Mahmoud Assran, Quentin Duval, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Michael Rabbat, Yann LeCun, Nicolas Ballas
ICML 2023 Self-Supervised Learning of Split Invariant Equivariant Representations Quentin Garrido, Laurent Najman, Yann Lecun
NeurIPS 2023 Self-Supervised Learning with Lie Symmetries for Partial Differential Equations Grégoire Mialon, Quentin Garrido, Hannah Lawrence, Danyal Rehman, Yann LeCun, Bobak Kiani
ICLRW 2023 Self-Supervised Learning with Lie Symmetries for Partial Differential Equations Grégoire Mialon, Quentin Garrido, Hannah Lawrence, Danyal Rehman, Yann LeCun, Bobak Kiani
ICML 2023 The SSL Interplay: Augmentations, Inductive Bias, and Generalization Vivien Cabannes, Bobak Kiani, Randall Balestriero, Yann Lecun, Alberto Bietti
ICLRW 2023 The SSL Interplay: Augmentations, Inductive Bias, and Generalization Vivien Cabannes, Bobak Kiani, Randall Balestriero, Yann LeCun, Alberto Bietti
TMLR 2023 VoLTA: Vision-Language Transformer with Weakly-Supervised Local-Feature Alignment Shraman Pramanick, Li Jing, Sayan Nag, Jiachen Zhu, Hardik J Shah, Yann LeCun, Rama Chellappa
NeurIPS 2022 A Data-Augmentation Is Worth a Thousand Samples: Analytical Moments and Sampling-Free Training Randall Balestriero, Ishan Misra, Yann LeCun
NeurIPS 2022 Coarse-to-Fine Vision-Language Pre-Training with Fusion in the Backbone 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
NeurIPS 2022 Contrastive and Non-Contrastive Self-Supervised Learning Recover Global and Local Spectral Embedding Methods Randall Balestriero, Yann LeCun
ECCV 2022 Decoupled Contrastive Learning Chun-Hsiao Yeh, Cheng-Yao Hong, Yen-Chi Hsu, Tyng-Luh Liu, Yubei Chen, Yann LeCun
ICMLW 2022 Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Prior Ravid Shwartz-Ziv, Micah Goldblum, Hossein Souri, Sanyam Kapoor, Chen Zhu, Yann LeCun, Andrew Gordon Wilson
NeurIPS 2022 Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors Ravid Shwartz-Ziv, Micah Goldblum, Hossein Souri, Sanyam Kapoor, Chen Zhu, Yann LeCun, Andrew G Wilson
ICLRW 2022 Separating the World and Ego Models for Self-Driving Vlad Sobal, Alfredo Canziani, Nicolas Carion, Kyunghyun Cho, Yann LeCun
TMLR 2022 Sparse Coding with Multi-Layer Decoders Using Variance Regularization Katrina Evtimova, Yann LeCun
NeurIPS 2022 The Effects of Regularization and Data Augmentation Are Class Dependent Randall Balestriero, Leon Bottou, Yann LeCun
ICLR 2022 Understanding Dimensional Collapse in Contrastive Self-Supervised Learning Li Jing, Pascal Vincent, Yann LeCun, Yuandong Tian
ICLR 2022 VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning Adrien Bardes, Jean Ponce, Yann LeCun
NeurIPS 2022 VICRegL: Self-Supervised Learning of Local Visual Features Adrien Bardes, Jean Ponce, Yann LeCun
ICMLW 2022 What Do We Maximize in Self-Supervised Learning? Ravid Shwartz-Ziv, Randall Balestriero, Yann LeCun
NeurIPS 2022 projUNN: Efficient Method for Training Deep Networks with Unitary Matrices Bobak Kiani, Randall Balestriero, Yann LeCun, Seth Lloyd
ICML 2021 Barlow Twins: Self-Supervised Learning via Redundancy Reduction Jure Zbontar, Li Jing, Ishan Misra, Yann LeCun, Stephane Deny
ICCV 2021 MDETR - Modulated Detection for End-to-End Multi-Modal Understanding Aishwarya Kamath, Mannat Singh, Yann LeCun, Gabriel Synnaeve, Ishan Misra, Nicolas Carion
NeurIPS 2020 Implicit Rank-Minimizing Autoencoder Li Jing, Jure Zbontar, Yann Lecun
ICLR 2019 Model-Predictive Policy Learning with Uncertainty Regularization for Driving in Dense Traffic Mikael Henaff, Alfredo Canziani, Yann LeCun
ICLR 2019 The Role of Over-Parametrization in Generalization of Neural Networks Behnam Neyshabur, Zhiyuan Li, Srinadh Bhojanapalli, Yann LeCun, Nathan Srebro
ICML 2018 Adversarially Regularized Autoencoders Junbo Zhao, Yoon Kim, Kelly Zhang, Alexander Rush, Yann LeCun
ICML 2018 Comparing Dynamics: Deep Neural Networks Versus Glassy Systems Marco Baity-Jesi, Levent Sagun, Mario Geiger, Stefano Spigler, Gerard Ben Arous, Chiara Cammarota, Yann LeCun, Matthieu Wyart, Giulio Biroli
ECCVW 2018 DesIGN: Design Inspiration from Generative Networks Othman Sbai, Mohamed Elhoseiny, Antoine Bordes, Yann LeCun, Camille Couprie
NeurIPS 2018 GLoMo: Unsupervised Learning of Transferable Relational Graphs Zhilin Yang, Jake Zhao, Bhuwan Dhingra, Kaiming He, William W. Cohen, Ruslan Salakhutdinov, Yann LeCun
ECCV 2018 Predicting Future Instance Segmentation by Forecasting Convolutional Features Pauline Luc, Camille Couprie, Yann LeCun, Jakob Verbeek
ICLR 2017 Energy-Based Generative Adversarial Networks Junbo Jake Zhao, Michaël Mathieu, Yann LeCun
ICLR 2017 Entropy-SGD: Biasing Gradient Descent into Wide Valleys Pratik Chaudhari, Anna Choromanska, Stefano Soatto, Yann LeCun, Carlo Baldassi, Christian Borgs, Jennifer T. Chayes, Levent Sagun, Riccardo Zecchina
ICCV 2017 Predicting Deeper into the Future of Semantic Segmentation Pauline Luc, Natalia Neverova, Camille Couprie, Jakob Verbeek, Yann LeCun
ICLR 2017 Tracking the World State with Recurrent Entity Networks Mikael Henaff, Jason Weston, Arthur Szlam, Antoine Bordes, Yann LeCun
ICML 2017 Tunable Efficient Unitary Neural Networks (EUNN) and Their Application to RNNs Li Jing, Yichen Shen, Tena Dubcek, John Peurifoy, Scott Skirlo, Yann LeCun, Max Tegmark, Marin Soljačić
AAAI 2017 Universum Prescription: Regularization Using Unlabeled Data Xiang Zhang, Yann LeCun
ICLR 2016 4th International Conference on Learning Representations, ICLR 2016, San Juan, Puerto Rico, May 2-4, 2016, Conference Track Proceedings Yoshua Bengio, Yann LeCun
ICML 2016 Binary Embeddings with Structured Hashed Projections Anna Choromanska, Krzysztof Choromanski, Mariusz Bojarski, Tony Jebara, Sanjiv Kumar, Yann LeCun
ICLR 2016 Deep Multi-Scale Video Prediction Beyond Mean Square Error Michaël Mathieu, Camille Couprie, Yann LeCun
NeurIPS 2016 Disentangling Factors of Variation in Deep Representation Using Adversarial Training Michael F Mathieu, Junbo Jake Zhao, Junbo Zhao, Aditya Ramesh, Pablo Sprechmann, Yann LeCun
ICML 2016 Recurrent Orthogonal Networks and Long-Memory Tasks Mikael Henaff, Arthur Szlam, Yann LeCun
MLOSS 2016 Stereo Matching by Training a Convolutional Neural Network to Compare Image Patches Jure Ćœbontar, Yann LeCun
ICLR 2016 Super-Resolution with Deep Convolutional Sufficient Statistics Joan Bruna, Pablo Sprechmann, Yann LeCun
ICLR 2015 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7-9, 2015, Conference Track Proceedings Yoshua Bengio, Yann LeCun
ICLR 2015 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7-9, 2015, Workshop Track Proceedings Yoshua Bengio, Yann LeCun
ICLR 2015 Audio Source Separation with Discriminative Scattering Networks Pablo Sprechmann, Joan Bruna, Yann LeCun
NeurIPS 2015 Character-Level Convolutional Networks for Text Classification Xiang Zhang, Junbo Zhao, Yann LeCun
CVPR 2015 Computing the Stereo Matching Cost with a Convolutional Neural Network Jure Zbontar, Yann LeCun
NeurIPS 2015 Deep Learning with Elastic Averaging SGD Sixin Zhang, Anna E Choromanska, Yann LeCun
ICLR 2015 Deep Learning with Elastic Averaging SGD Sixin Zhang, Anna Choromanska, Yann LeCun
CVPR 2015 Efficient Object Localization Using Convolutional Networks Jonathan Tompson, Ross Goroshin, Arjun Jain, Yann LeCun, Christoph Bregler
ICLR 2015 Explorations on High Dimensional Landscapes Levent Sagun, V. Ugur GĂŒney, Yann LeCun
ICLR 2015 Fast Convolutional Nets with Fbfft: A GPU Performance Evaluation Nicolas Vasilache, Jeff Johnson, Michaël Mathieu, Soumith Chintala, Serkan Piantino, Yann LeCun
NeurIPS 2015 Learning to Linearize Under Uncertainty Ross Goroshin, Michael F Mathieu, Yann LeCun
COLT 2015 Open Problem: The Landscape of the Loss Surfaces of Multilayer Networks Anna Choromanska, Yann LeCun, Gérard Ben Arous
AISTATS 2015 The Loss Surfaces of Multilayer Networks Anna Choromanska, Mikael Henaff, Michaël Mathieu, Gérard Ben Arous, Yann LeCun
ICLR 2015 Unsupervised Feature Learning from Temporal Data Ross Goroshin, Joan Bruna, Jonathan Tompson, David Eigen, Yann LeCun
ICCV 2015 Unsupervised Learning of Spatiotemporally Coherent Metrics Ross Goroshin, Joan Bruna, Jonathan Tompson, David Eigen, Yann LeCun
ICLR 2014 2nd International Conference on Learning Representations, ICLR 2014, Banff, AB, Canada, April 14-16, 2014, Conference Track Proceedings Yoshua Bengio, Yann LeCun
ICLR 2014 2nd International Conference on Learning Representations, ICLR 2014, Banff, AB, Canada, April 14-16, 2014, Workshop Track Proceedings Yoshua Bengio, Yann LeCun
JMLR 2014 Convolutional Nets and Watershed Cuts for Real-Time Semantic Labeling of RGBD Videos Camille Couprie, Clément Farabet, Laurent Najman, Yann LeCun
NeurIPS 2014 Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation Emily L Denton, Wojciech Zaremba, Joan Bruna, Yann LeCun, Rob Fergus
ICLR 2014 Fast Training of Convolutional Networks Through FFTs Michaël Mathieu, Mikael Henaff, Yann LeCun
NeurIPS 2014 Joint Training of a Convolutional Network and a Graphical Model for Human Pose Estimation Jonathan J Tompson, Arjun Jain, Yann LeCun, Christoph Bregler
ICLR 2014 OverFeat: Integrated Recognition, Localization and Detection Using Convolutional Networks Pierre Sermanet, David Eigen, Xiang Zhang, Michaël Mathieu, Rob Fergus, Yann LeCun
ICML 2014 Signal Recovery from Pooling Representations Joan Bruna Estrach, Arthur Szlam, Yann LeCun
ICLR 2014 Spectral Networks and Locally Connected Networks on Graphs Joan Bruna, Wojciech Zaremba, Arthur Szlam, Yann LeCun
ICLR 2014 Understanding Deep Architectures Using a Recursive Convolutional Network David Eigen, Jason Tyler Rolfe, Rob Fergus, Yann LeCun
ICLR 2013 1st International Conference on Learning Representations, ICLR 2013, Scottsdale, Arizona, USA, May 2-4, 2013, Conference Track Proceedings Yoshua Bengio, Yann LeCun
ICLR 2013 1st International Conference on Learning Representations, ICLR 2013, Scottsdale, Arizona, USA, May 2-4, 2013, Workshop Track Proceedings Yoshua Bengio, Yann LeCun
ICLR 2013 Adaptive Learning Rates and Parallelization for Stochastic, Sparse, Non-Smooth Gradients Tom Schaul, Yann LeCun
ICLR 2013 Discriminative Recurrent Sparse Auto-Encoders Jason Tyler Rolfe, Yann LeCun
ICLR 2013 Indoor Semantic Segmentation Using Depth Information Camille Couprie, Clément Farabet, Laurent Najman, Yann LeCun
ICLR 2013 Learning Stable Group Invariant Representations with Convolutional Networks Joan Bruna, Arthur Szlam, Yann LeCun
ICML 2013 No More Pesky Learning Rates Tom Schaul, Sixin Zhang, Yann LeCun
CVPR 2013 Pedestrian Detection with Unsupervised Multi-Stage Feature Learning Pierre Sermanet, Koray Kavukcuoglu, Soumith Chintala, Yann Lecun
ICLR 2013 Pushing Stochastic Gradient Towards Second-Order Methods -- Backpropagation Learning with Transformations in Nonlinearities Tommi Vatanen, Tapani Raiko, Harri Valpola, Yann LeCun
ICLR 2013 Saturating Auto-Encoder Rostislav Goroshin, Yann LeCun
AISTATS 2012 Deep Learning Made Easier by Linear Transformations in Perceptrons Tapani Raiko, Harri Valpola, Yann Lecun
ECCV 2012 Fast Approximations to Structured Sparse Coding and Applications to Object Classification Arthur Szlam, Karol Gregor, Yann LeCun
ECCV 2012 Learning Invariant Feature Hierarchies Yann LeCun
ECCVW 2012 Learning Invariant Feature Hierarchies Yann LeCun
ECCV 2012 Road Scene Segmentation from a Single Image José M. Álvarez, Theo Gevers, Yann LeCun, Antonio M. López
ICML 2012 Scene Parsing with Multiscale Feature Learning, Purity Trees, and Optimal Covers Clément Farabet, Camille Couprie, Laurent Najman, Yann LeCun
ECCV 2012 Semantic Road Segmentation via Multi-Scale Ensembles of Learned Features José M. Álvarez, Yann LeCun, Theo Gevers, Antonio M. López
ECCVW 2012 Semantic Road Segmentation via Multi-Scale Ensembles of Learned Features José M. Álvarez, Yann LeCun, Theo Gevers, Antonio M. López
ICCV 2011 Ask the Locals: Multi-Way Local Pooling for Image Recognition Y-Lan Boureau, Nicolas Le Roux, Francis R. Bach, Jean Ponce, Yann LeCun
CVPRW 2011 NeuFlow: A Runtime Reconfigurable Dataflow Processor for Vision Clément Farabet, Berin Martini, B. Corda, Polina Akselrod, Eugenio Culurciello, Yann LeCun
ICML 2010 A Theoretical Analysis of Feature Pooling in Visual Recognition Y-Lan Boureau, Jean Ponce, Yann LeCun
ECCV 2010 Convolutional Learning of Spatio-Temporal Features Graham W. Taylor, Rob Fergus, Yann LeCun, Christoph Bregler
ICML 2010 Learning Fast Approximations of Sparse Coding Karol Gregor, Yann LeCun
CVPR 2010 Learning Mid-Level Features for Recognition Y-Lan Boureau, Francis R. Bach, Yann LeCun, Jean Ponce
ICCVW 2009 An FPGA-Based Stream Processor for Embedded Real-Time Vision with Convolutional Networks Clément Farabet, Cyril Poulet, Yann LeCun
ECML-PKDD 2009 Dynamic Factor Graphs for Time Series Modeling Piotr Mirowski, Yann LeCun
CVPR 2009 Learning Invariant Features Through Topographic Filter Maps Koray Kavukcuoglu, Marc'Aurelio Ranzato, Rob Fergus, Yann LeCun
ICCV 2009 What Is the Best Multi-Stage Architecture for Object Recognition? Kevin Jarrett, Koray Kavukcuoglu, Marc'Aurelio Ranzato, Yann LeCun
ICML 2009 Workshop Summary: Workshop on Learning Feature Hierarchies Kai Yu, Ruslan Salakhutdinov, Yann LeCun, Geoffrey E. Hinton, Yoshua Bengio
AISTATS 2007 A Unified Energy-Based Framework for Unsupervised Learning Marc’Aurelio Ranzato, Y-Lan Boureau, Sumit Chopra, Yann LeCun
JMLR 2007 The Need for Open Source Software in Machine Learning Sören Sonnenburg, Mikio L. Braun, Cheng Soon Ong, Samy Bengio, Leon Bottou, Geoffrey Holmes, Yann LeCun, Klaus-Robert MĂŒller, Fernando Pereira, Carl Edward Rasmussen, Gunnar RĂ€tsch, Bernhard Schölkopf, Alexander Smola, Pascal Vincent, Jason Weston, Robert Williamson
AAAI 2007 Time-Delay Neural Networks and Independent Component Analysis for EEG-Based Prediction of Epileptic Seizures Propagation Piotr W. Mirowski, Deepak Madhavan, Yann LeCun
CVPR 2007 Unsupervised Learning of Invariant Feature Hierarchies with Applications to Object Recognition Marc'Aurelio Ranzato, Fu Jie Huang, Y-Lan Boureau, Yann LeCun
CVPR 2006 Dimensionality Reduction by Learning an Invariant Mapping Raia Hadsell, Sumit Chopra, Yann LeCun
CVPR 2006 Large-Scale Learning with SVM and Convolutional for Generic Object Categorization Fu Jie Huang, Yann LeCun
CVPR 2005 Learning a Similarity Metric Discriminatively, with Application to Face Verification Sumit Chopra, Raia Hadsell, Yann LeCun
AISTATS 2005 Loss Functions for Discriminative Training of Energy-Based Models Yann LeCun, Fu Jie Huang
CVPR 2004 Learning Methods for Generic Object Recognition with Invariance to Pose and Lighting Yann LeCun, Fu Jie Huang, Léon Bottou
NeurIPS 1998 Boxlets: A Fast Convolution Algorithm for Signal Processing and Neural Networks Patrice Simard, Léon Bottou, Patrick Haffner, Yann LeCun
CVPR 1997 Global Training of Document Processing Systems Using Graph Transformer Networks Léon Bottou, Yoshua Bengio, Yann LeCun
NeCo 1995 LeRec: A NN/HMM Hybrid for On-Line Handwriting Recognition Yoshua Bengio, Yann LeCun, Craig R. Nohl, Christopher J. C. Burges
NeCo 1994 Boosting and Other Ensemble Methods Harris Drucker, Corinna Cortes, Lawrence D. Jackel, Yann LeCun, Vladimir Vapnik
ICML 1994 Boosting and Other Machine Learning Algorithms Harris Drucker, Corinna Cortes, Lawrence D. Jackel, Yann LeCun, Vladimir Vapnik
NeCo 1994 Measuring the VC-Dimension of a Learning Machine Vladimir Vapnik, Esther Levin, Yann LeCun
NeurIPS 1993 Globally Trained Handwritten Word Recognizer Using Spatial Representation, Convolutional Neural Networks, and Hidden Markov Models Yoshua Bengio, Yann LeCun, Donnie Henderson
NeurIPS 1993 Signature Verification Using a "Siamese" Time Delay Neural Network Jane Bromley, Isabelle Guyon, Yann LeCun, Eduard SĂ€ckinger, Roopak Shah
NeurIPS 1992 Automatic Learning Rate Maximization by On-Line Estimation of the Hessian's Eigenvectors Yann LeCun, Patrice Y. Simard, Barak Pearlmutter
NeurIPS 1992 Efficient Pattern Recognition Using a New Transformation Distance Patrice Simard, Yann LeCun, John S. Denker
NeurIPS 1991 Multi-Digit Recognition Using a Space Displacement Neural Network Ofer Matan, Christopher J. C. Burges, Yann LeCun, John S. Denker
NeurIPS 1991 Tangent Prop - A Formalism for Specifying Selected Invariances in an Adaptive Network Patrice Simard, Bernard Victorri, Yann LeCun, John Denker
NeurIPS 1990 Second Order Properties of Error Surfaces: Learning Time and Generalization Yann LeCun, Ido Kanter, Sara A. Solla
NeurIPS 1990 Transforming Neural-Net Output Levels to Probability Distributions John S. Denker, Yann LeCun
NeCo 1989 Backpropagation Applied to Handwritten Zip Code Recognition Yann LeCun, Bernhard E. Boser, John S. Denker, Donnie Henderson, Richard E. Howard, Wayne E. Hubbard, Lawrence D. Jackel
NeurIPS 1989 Handwritten Digit Recognition with a Back-Propagation Network Yann LeCun, Bernhard E. Boser, John S. Denker, Donnie Henderson, R. E. Howard, Wayne E. Hubbard, Lawrence D. Jackel
NeurIPS 1989 Optimal Brain Damage Yann LeCun, John S. Denker, Sara A. Solla