GEMINI: Gradient Estimation Through Matrix Inversion After Noise Injection. - Yann LeCun; Conrad C. Galland; Geoffrey E. Hinton (NIPS, 1988)

Using curvature information to improve back-propagation. - Yann LeCun (Neural Networks, 1988)

Handwritten Digit Recognition: Applications of Neural Net Chips and Automatic Learning. - Yann LeCun; Larry D. Jackel; Bernhard E. Boser; John S. Denker; Hans Peter Graf; Isabelle Guyon; Donnie Henderson; Richard E. Howard; Wayne E. Hubbard (NATO Neurocomputing, 1989)

Handwritten Digit Recognition with a Back-Propagation Network. - Yann LeCun; Bernhard E. Boser; John S. Denker; Donnie Henderson; Richard E. Howard; Wayne E. Hubbard; Lawrence D. Jackel (NIPS, 1989)

Optimal Brain Damage. - Yann LeCun; John S. Denker; Sara A. Solla (NIPS, 1989)

Handwritten digit recognition: applications of neural network chips and automatic learning. - Yann LeCun; Lawrence D. Jackel; Bernhard E. Boser; John S. Denker; Hans Peter Graf; Isabelle Guyon; Don Henderson; Richard E. Howard; Wayne E. Hubbard (IEEE Commun. Mag., 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 (Neural Comput., 1989)

Handwritten zip code recognition with multilayer networks. - Yann LeCun; Ofer Matan; Bernhard E. Boser; John S. Denker; Don Henderson; Richard E. Howard; Wayne E. Hubbard; L. D. Jacket; Henry S. Baird (ICPR (2), 1990)

Hardware requirements for neural-net optical character recognition. - 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 (IJCNN, 1990)

Second Order Properties of Error Surfaces. - Yann LeCun; Ido Kanter; Sara A. Solla (NIPS, 1990)

Transforming Neural-Net Output Levels to Probability Distributions. - John S. Denker; Yann LeCun (NIPS, 1990)

A neural network approach to handprint character recognition. - 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; et al. (Compcon, 1991)

Multi-Digit Recognition Using a Space Displacement Neural Network. - Ofer Matan; Christopher J. C. Burges; Yann LeCun; John S. Denker (NIPS, 1991)

Reverse TDNN: An Architecture For Trajectory Generation. - Patrice Y. Simard; Yann LeCun (NIPS, 1991)

Tangent Prop - A Formalism for Specifying Selected Invariances in an Adaptive Network. - Patrice Y. Simard; Bernard Victorri; Yann LeCun; John S. Denker (NIPS, 1991)

Design of a neural network character recognizer for a touch terminal. - Isabelle Guyon; P. Albrecht; Yann LeCun; John S. Denker; Wayne E. Hubbard (Pattern Recognit., 1991)

An analog neural network processor with programmable topology. - Bernhard E. Boser; Eduard Sackinger; Jane Bromley; Yann LeCun; Lawrence D. Jackel (IEEE J. Solid State Circuits, 1991)

An efficient algorithm for learning invariance in adaptive classifiers. - Patrice Y. Simard; Yann LeCun; John S. Denker; Bernard Victorri (ICPR (2), 1992)

Automatic Learning Rate Maximization in Large Adaptive Machines. - Yann LeCun; Patrice Y. Simard; Barak A. Pearlmutter (NIPS, 1992)

Efficient Pattern Recognition Using a New Transformation Distance. - Patrice Y. Simard; Yann LeCun; John S. Denker (NIPS, 1992)

Reading Handwritten Digits: A ZIP Code Recognition System. - 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 (Computer, 1992)

Hardware requirements for neural network pattern classifiers: a case study and implementation. - Bernhard E. Boser; Eduard Säckinger; Jane Bromley; Yann LeCun; Lawrence D. Jackel (IEEE Micro, 1992)

Improving generalization performance using double backpropagation. - Harris Drucker; Yann LeCun (IEEE Trans. Neural Networks, 1992)

Application of the ANNA neural network chip to high-speed character recognition. - Eduard Säckinger; Bernhard E. Boser; Jane Bromley; Yann LeCun; Lawrence D. Jackel (IEEE Trans. Neural Networks, 1992)

On-line recognition of limited-vocabulary Chinese character using multiple convolutional neural networks. - Quen-Zong Wu; Yann LeCun; Lawrence D. Jackel; Bor-Shenn Jeng (ISCAS, 1993)

Globally Trained Handwritten Word Recognizer Using Spatial Representation, Convolutional Neural Networks, and Hidden Markov Models. - Yoshua Bengio; Yann LeCun; Donnie Henderson (NIPS, 1993)

Signature Verification Using a Siamese Time Delay Neural Network. - Jane Bromley; Isabelle Guyon; Yann LeCun; Eduard Säckinger; Roopak Shah (NIPS, 1993)

Signature Verification Using A "Siamese" Time Delay Neural Network. - Jane Bromley; James W. Bentz; Léon Bottou; Isabelle Guyon; Yann LeCun; Cliff Moore; Eduard Säckinger; Roopak Shah (Int. J. Pattern Recognit. Artif. Intell., 1993)

Off Line Recognition of Handwritten Postal Words Using Neural Networks. - Christopher J. C. Burges; Jan Ben; John S. Denker; Yann LeCun; Craig R. Nohl (Int. J. Pattern Recognit. Artif. Intell., 1993)

Boosting and Other Machine Learning Algorithms. - Harris Drucker; Corinna Cortes; Lawrence D. Jackel; Yann LeCun; Vladimir Vapnik (ICML, 1994)

Word normalization for online handwritten word recognition. - Yoshua Bengio; Yann LeCun (ICPR (2), 1994)

Comparison of classifier methods: a case study in handwritten digit recognition. - 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 (ICPR (2), 1994)

Word-level training of a handwritten word recognizer based on convolutional neural networks. - Yann LeCun; Yoshua Bengio (ICPR (2), 1994)

Memory-based character recognition using a transformation invariant metric. - Patrice Y. Simard; Yann LeCun; John S. Denker (ICPR (2), 1994)

Boosting and Other Ensemble Methods. - Harris Drucker; Corinna Cortes; Lawrence D. Jackel; Yann LeCun; Vladimir Vapnik (Neural Comput., 1994)

Measuring the VC-Dimension of a Learning Machine. - Vladimir Vapnik; Esther Levin; Yann LeCun (Neural Comput., 1994)

LeRec: a NN/HMM hybrid for on-line handwriting recognition. - Yoshua Bengio; Yann LeCun; Craig R. Nohl; Christopher J. C. Burges (Neural Comput., 1995)

Effiicient BackProp. - Yann LeCun; Léon Bottou; Genevieve B. Orr; Klaus-Robert Müller (Neural Networks: Tricks of the Trade, 1996)

Transformation Invariance in Pattern Recognition-Tangent Distance and Tangent Propagation. - Patrice Y. Simard; Yann LeCun; John S. Denker; Bernard Victorri (Neural Networks: Tricks of the Trade, 1996)

Global Training of Document Processing Systems Using Graph Transformer Networks. - Léon Bottou; Yoshua Bengio; Yann LeCun (CVPR, 1997)

Reading checks with multilayer graph transformer networks. - Yann LeCun; Léon Bottou; Yoshua Bengio (ICASSP, 1997)

On the Applications of Multimedia Processing to Telecommunications. - Richard V. Cox; Barry G. Haskell; Yann LeCun; Behzad Shahraray; Lawrence R. Rabiner (ICIP (1), 1997)

Discriminative feature and model design for automatic speech recognition. - Mazin Rahim; Yoshua Bengio; Yann LeCun (EUROSPEECH, 1997)

Browsing through High Quality Document Images with DjVu. - Patrick Haffner; Léon Bottou; Paul G. Howard; Patrice Y. Simard; Yoshua Bengio; Yann LeCun (ADL, 1998)

DjVu: a Compression Method for Distributing Scanned Documents in Color over the Internet. - Yann LeCun; Léon Bottou; Patrick Haffner; Paul G. Howard (CIC, 1998)

Boxlets: A Fast Convolution Algorithm for Signal Processing and Neural Networks. - Patrice Y. Simard; Léon Bottou; Patrick Haffner; Yann LeCun (NIPS, 1998)

High quality document image compression with "DjVu". - Léon Bottou; Patrick Haffner; Paul G. Howard; Patrice Y. Simard; Yoshua Bengio; Yann LeCun (J. Electronic Imaging, 1998)

On the applications of multimedia processing to communications. - Richard V. Cox; Barry G. Haskell; Yann LeCun; Behzad Shahraray; Lawrence R. Rabiner (Proc. IEEE, 1998)

Gradient-based learning applied to document recognition. - Yann LeCun; Léon Bottou; Yoshua Bengio; Patrick Haffner (Proc. IEEE, 1998)

Image and video coding-emerging standards and beyond. - Barry G. Haskell; Paul G. Howard; Yann LeCun; Atul Puri; Jörn Ostermann; M. Reha Civanlar; Lawrence R. Rabiner; Léon Bottou; Patrick Haffner (IEEE Trans. Circuits Syst. Video Technol., 1998)

Guest Editorial Applications Of Artificial Neural Networks To Image Processing. - Rama Chellappa; Kunihiko Fukushima; Aggelos K. Katsaggelos; Sun-Yuan Kung; Yann LeCun; Nasser M. Nasrabadi; Tomaso A. Poggio (IEEE Trans. Image Process., 1998)

DjVu: Analyzing and Compressing Scanned Documents for Internet Distribution. - Patrick Haffner; Léon Bottou; Paul G. Howard; Yann LeCun (ICDAR, 1999)

Color Documents on the Web with DJVU. - Patrick Haffner; Yann LeCun; Léon Bottou; Paul G. Howard; Pascal Vincent; Bill Riemers (ICIP (1), 1999)

Object Recognition with Gradient-Based Learning. - Yann LeCun; Patrick Haffner; Léon Bottou; Yoshua Bengio (Shape, Contour and Grouping in Computer Vision, 1999)

Transformation invariance in pattern recognition: Tangent distance and propagation. - Patrice Y. Simard; Yann LeCun; John S. Denker; Bernard Victorri (Int. J. Imaging Syst. Technol., 2000)

Efficient Conversion of Digital Documents to Multilayer Raster Formats. - Léon Bottou; Patrick Haffner; Yann LeCun (ICDAR, 2001)

Real Time Voice Processing with Audiovisual Feedback: Toward Autonomous Agents with Perfect Pitch. - Lawrence K. Saul; Daniel D. Lee; Charles L. Isbell Jr.; Yann LeCun (NIPS, 2002)

Large Scale Online Learning. - Léon Bottou; Yann LeCun (NIPS, 2003)

Learning Methods for Generic Object Recognition with Invariance to Pose and Lighting. - Yann LeCun; Fu Jie Huang; Léon Bottou (CVPR (2), 2004)

Loss Functions for Discriminative Training of Energy-Based Models. - Yann LeCun; Fu Jie Huang (AISTATS, 2005)

Learning a Similarity Metric Discriminatively, with Application to Face Verification. - Sumit Chopra; Raia Hadsell; Yann LeCun (CVPR (1), 2005)

Off-Road Obstacle Avoidance through End-to-End Learning. - Yann LeCun; Urs Muller; Jan Ben; Eric Cosatto; Beat Flepp (NIPS, 2005)

Toward Automatic Phenotyping of Developing Embryos From Videos. - F. Ning; D. Delhomme; Yann LeCun; F. Piano; Léon Bottou; Paolo Emilio Barbano (IEEE Trans. Image Process., 2005)

Dimensionality Reduction by Learning an Invariant Mapping. - Raia Hadsell; Sumit Chopra; Yann LeCun (CVPR (2), 2006)

Large-scale Learning with SVM and Convolutional for Generic Object Categorization. - Fu Jie Huang; Yann LeCun (CVPR (1), 2006)

Efficient Learning of Sparse Representations with an Energy-Based Model. - Marc'Aurelio Ranzato; Christopher S. Poultney; Sumit Chopra; Yann LeCun (NIPS, 2006)

Time-Delay Neural Networks and Independent Component Analysis for EEG-Based Prediction of Epileptic Seizures Propagation. - Piotr W. Mirowski; Deepak Madhavan; Yann LeCun (AAAI, 2007)

Unsupervised Learning of Invariant Feature Hierarchies with Applications to Object Recognition. - Marc'Aurelio Ranzato; Fu Jie Huang; Y-Lan Boureau; Yann LeCun (CVPR, 2007)

Energy-Based Models in Document Recognition and Computer Vision. - Yann LeCun; Sumit Chopra; Marc'Aurelio Ranzato; Fu Jie Huang (ICDAR, 2007)

A Sparse and Locally Shift Invariant Feature Extractor Applied to Document Images. - Marc'Aurelio Ranzato; Yann LeCun (ICDAR, 2007)

Adaptive long range vision in unstructured terrain. - Ayse Erkan; Raia Hadsell; Pierre Sermanet; Jan Ben; Urs Muller; Yann LeCun (IROS, 2007)

Discovering the hidden structure of house prices with a non-parametric latent manifold model. - Sumit Chopra; Trivikraman Thampy; John Leahy; Andrew Caplin; Yann LeCun (KDD, 2007)

Sparse Feature Learning for Deep Belief Networks. - Marc'Aurelio Ranzato; Y-Lan Boureau; Yann LeCun (NIPS, 2007)

Online Learning for Offroad Robots: Spatial Label Propagation to Learn Long-Range Traversability. - Raia Hadsell; Pierre Sermanet; Jan Ben; Ayse Erkan; Jeff Han; Urs Muller; Yann LeCun (Robotics: Science and Systems, 2007)

Synergistic Face Detection and Pose Estimation with Energy-Based Models. - Margarita Osadchy; Yann LeCun; Matthew L. Miller (J. Mach. Learn. Res., 2007)

A Unified Energy-Based Framework for Unsupervised Learning. - Marc'Aurelio Ranzato; Y-Lan Boureau; Sumit Chopra; Yann LeCun (AISTATS, 2007)

The Need for Open Source Software in Machine Learning. - Sören Sonnenburg; Mikio L. Braun; Cheng Soon Ong; Samy Bengio; Léon Bottou; Geoffrey Holmes 001; Yann LeCun; Klaus-Robert Müller; Fernando Pereira 003; Carl Edward Rasmussen; Gunnar Rätsch; Bernhard Schölkopf; et al. (J. Mach. Learn. Res., 2007)

Automatic recognition of biological particles in microscopic images. - Marc'Aurelio Ranzato; P. E. Taylor; James M. House; R. C. Flagan; Yann LeCun; Pietro Perona (Pattern Recognit. Lett., 2007)

Deep belief net learning in a long-range vision system for autonomous off-road driving. - Raia Hadsell; Ayse Erkan; Pierre Sermanet; Marco Scoffier; Urs Muller; Yann LeCun (IROS, 2008)

Mapping and planning under uncertainty in mobile robots with long-range perception. - Pierre Sermanet; Raia Hadsell; Marco Scoffier; Urs Muller; Yann LeCun (IROS, 2008)

Editorial. - Andrew W. Fitzgibbon; Camillo J. Taylor; Yann LeCun (Int. J. Comput. Vis., 2008)

Learning invariant features through topographic filter maps. - Koray Kavukcuoglu; Marc'Aurelio Ranzato; Rob Fergus; Yann LeCun (CVPR, 2009)

CNP: An FPGA-based processor for Convolutional Networks. - Clément Farabet; Cyril Poulet; Jefferson Y. Han; Yann LeCun (FPL, 2009)

What is the best multi-stage architecture for object recognition? - Kevin Jarrett; Koray Kavukcuoglu; Marc'Aurelio Ranzato; Yann LeCun (ICCV, 2009)

An FPGA-based stream processor for embedded real-time vision with Convolutional Networks. - Clément Farabet; Cyril Poulet; Yann LeCun (ICCV Workshops, 2009)

Workshop summary: Workshop on learning feature hierarchies. - Kai Yu; Ruslan Salakhutdinov; Yann LeCun; Geoffrey E. Hinton; Yoshua Bengio (ICML, 2009)

Efficient off-road localization using visually corrected odometry. - Matthew Grimes; Yann LeCun (ICRA, 2009)

EBLearn: Open-Source Energy-Based Learning in C++. - Pierre Sermanet; Koray Kavukcuoglu; Yann LeCun (ICTAI, 2009)

Dynamic Factor Graphs for Time Series Modeling. - Piotr Mirowski; Yann LeCun (ECML/PKDD (2), 2009)

Learning long-range vision for autonomous off-road driving. - Raia Hadsell; Pierre Sermanet; Jan Ben; Ayse Erkan; Marco Scoffier; Koray Kavukcuoglu; Urs Muller; Yann LeCun (J. Field Robotics, 2009)

A multirange architecture for collision-free off-road robot navigation. - Pierre Sermanet; Raia Hadsell; Marco Scoffier; Matthew Grimes; Jan Ben; Ayse Erkan; Chris Crudele; Urs Miller; Yann LeCun (J. Field Robotics, 2009)

Learning mid-level features for recognition. - Y-Lan Boureau; Francis R. Bach; Yann LeCun; Jean Ponce (CVPR, 2010)

Convolutional Learning of Spatio-temporal Features. - Graham W. Taylor; Rob Fergus; Yann LeCun; Christoph Bregler (ECCV (6), 2010)

A Theoretical Analysis of Feature Pooling in Visual Recognition. - Y-Lan Boureau; Jean Ponce; Yann LeCun (ICML, 2010)

Learning Fast Approximations of Sparse Coding. - Karol Gregor; Yann LeCun (ICML, 2010)

Hybrid hessians for flexible optimization of pose graphs. - Matthew Koichi Grimes; Dragomir Anguelov; Yann LeCun (IROS, 2010)

Hardware accelerated convolutional neural networks for synthetic vision systems. - Clément Farabet; Berin Martini; Polina Akselrod; Selçuk Talay; Yann LeCun; Eugenio Culurciello (ISCAS, 2010)

Convolutional networks and applications in vision. - Yann LeCun; Koray Kavukcuoglu; Clément Farabet (ISCAS, 2010)

Learning Convolutional Feature Hierarchies for Visual Recognition. - Koray Kavukcuoglu; Pierre Sermanet; Y-Lan Boureau; Karol Gregor; Michaël Mathieu; Yann LeCun (NIPS, 2010)

Regularized estimation of image statistics by Score Matching. - Diederik P. Kingma; Yann LeCun (NIPS, 2010)

Emergence of Complex-Like Cells in a Temporal Product Network with Local Receptive Fields - Karol Gregor; Yann LeCun (CoRR, 2010)

Convolutional Matching Pursuit and Dictionary Training - Arthur Szlam; Koray Kavukcuoglu; Yann LeCun (CoRR, 2010)

Fast Inference in Sparse Coding Algorithms with Applications to Object Recognition - Koray Kavukcuoglu; Marc'Aurelio Ranzato; Yann LeCun (CoRR, 2010)

Hardware accelerated visual attention algorithm. - Polina Akselrod; Faye Zhao; Ifigeneia Derekli; Clément Farabet; Berin Martini; Yann LeCun; Eugenio Culurciello (CISS, 2011)

NeuFlow: A runtime reconfigurable dataflow processor for vision. - Clément Farabet; Berin Martini; B. Corda; Polina Akselrod; Eugenio Culurciello; Yann LeCun (CVPR Workshops, 2011)

Ask the locals: Multi-way local pooling for image recognition. - Y-Lan Boureau; Nicolas Le Roux; Francis R. Bach; Jean Ponce; Yann LeCun (ICCV, 2011)

Traffic sign recognition with multi-scale Convolutional Networks. - Pierre Sermanet; Yann LeCun (IJCNN, 2011)

Unsupervised Learning of Sparse Features for Scalable Audio Classification. - Mikael Henaff; Kevin Jarrett; Koray Kavukcuoglu; Yann LeCun (ISMIR, 2011)

Structured sparse coding via lateral inhibition. - Arthur Szlam; Karol Gregor; Yann LeCun (NIPS, 2011)

Concerto for violin and Markov model: technical perspective. - Juan Pablo Bello; Yann LeCun; Robert Rowe (Commun. ACM, 2011)

Efficient Learning of Sparse Invariant Representations - Karol Gregor; Yann LeCun (CoRR, 2011)

Learning Representations by Maximizing Compression - Karol Gregor; Yann LeCun (CoRR, 2011)

Road Scene Segmentation from a Single Image. - José M. Álvarez 004; Theo Gevers; Yann LeCun; Antonio M. López 001 (ECCV (7), 2012)

Semantic Road Segmentation via Multi-scale Ensembles of Learned Features. - José M. Álvarez 004; Yann LeCun; Theo Gevers; Antonio M. López 001 (ECCV Workshops (2), 2012)

Learning Invariant Feature Hierarchies. - Yann LeCun (ECCV Workshops (1), 2012)

Fast Approximations to Structured Sparse Coding and Applications to Object Classification. - Arthur Szlam; Karol Gregor; Yann LeCun (ECCV (5), 2012)

Scene parsing with Multiscale Feature Learning, Purity Trees, and Optimal Covers. - Clément Farabet; Camille Couprie; Laurent Najman; Yann LeCun (ICML, 2012)

Convolutional neural networks applied to house numbers digit classification. - Pierre Sermanet; Soumith Chintala; Yann LeCun (ICPR, 2012)

Moving Beyond Feature Design: Deep Architectures and Automatic Feature Learning in Music Informatics. - Eric J. Humphrey; Juan Pablo Bello; Yann LeCun (ISMIR, 2012)

NeuFlow: Dataflow vision processing system-on-a-chip. - Phi-Hung Pham; Darko Jelaca; Clément Farabet; Berin Martini; Yann LeCun; Eugenio Culurciello (MWSCAS, 2012)

Deep Learning Made Easier by Linear Transformations in Perceptrons. - Tapani Raiko; Harri Valpola; Yann LeCun (AISTATS, 2012)

Efficient BackProp. - Yann LeCun; Léon Bottou; Genevieve B. Orr; Klaus-Robert Müller (Neural Networks: Tricks of the Trade (2nd ed.), 2012)

Transformation Invariance in Pattern Recognition - Tangent Distance and Tangent Propagation. - Patrice Y. Simard; Yann LeCun; John S. Denker; Bernard Victorri (Neural Networks: Tricks of the Trade (2nd ed.), 2012)

Preface. - Marc Pickett; Benjamin Kuipers; Yann LeCun; Clayton T. Morrison (AAAI Workshop: Learning Rich Representations from Low-Level Sensors, 2013)

Pedestrian Detection with Unsupervised Multi-stage Feature Learning. - Pierre Sermanet; Koray Kavukcuoglu; Soumith Chintala; Yann LeCun (CVPR, 2013)

Causal graph-based video segmentation. - Camille Couprie; Clément Farabet; Yann LeCun; Laurent Najman (ICIP, 2013)

No more pesky learning rates. - Tom Schaul; Sixin Zhang; Yann LeCun (ICML (3), 2013)

Regularization of Neural Networks using DropConnect. - Li Wan 002; Matthew D. Zeiler; Sixin Zhang; Yann LeCun; Rob Fergus (ICML (3), 2013)

Causal graph-based video segmentation - Camille Couprie; Clément Farabet; Yann LeCun (CoRR, 2013)

Pushing Stochastic Gradient towards Second-Order Methods – Backpropagation Learning with Transformations in Nonlinearities - Tommi Vatanen; Tapani Raiko; Harri Valpola; Yann LeCun (ICLR (Workshop Poster), 2013)

Learning Stable Group Invariant Representations with Convolutional Networks - Joan Bruna; Arthur Szlam; Yann LeCun (ICLR (Workshop Poster), 2013)

Indoor Semantic Segmentation using depth information - Camille Couprie; Clément Farabet; Laurent Najman; Yann LeCun (ICLR, 2013)

Saturating Auto-Encoder - Rostislav Goroshin; Yann LeCun (ICLR (Poster), 2013)

Adaptive learning rates and parallelization for stochastic, sparse, non-smooth gradients - Tom Schaul; Yann LeCun (ICLR (Poster), 2013)

Discriminative Recurrent Sparse Auto-Encoders - Jason Tyler Rolfe; Yann LeCun (ICLR, 2013)

Feature learning and deep architectures: new directions for music informatics. - Eric J. Humphrey; Juan Pablo Bello; Yann LeCun (J. Intell. Inf. Syst., 2013)

Learning Hierarchical Features for Scene Labeling. - Clément Farabet; Camille Couprie; Laurent Najman; Yann LeCun (IEEE Trans. Pattern Anal. Mach. Intell., 2013)

MoDeep: A Deep Learning Framework Using Motion Features for Human Pose Estimation. - Arjun Jain; Jonathan Tompson; Yann LeCun; Christoph Bregler (ACCV (2), 2014)

Signal recovery from Pooling Representations. - Joan Bruna Estrach; Arthur Szlam; Yann LeCun (ICML, 2014)

Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation. - Emily L. Denton; Wojciech Zaremba; Joan Bruna; Yann LeCun; Rob Fergus (NIPS, 2014)

Joint Training of a Convolutional Network and a Graphical Model for Human Pose Estimation. - Jonathan Tompson; Arjun Jain; Yann LeCun; Christoph Bregler (NIPS, 2014)

Differentially- and non-differentially-private random decision trees. - Mariusz Bojarski; Anna Choromanska; Krzysztof Choromanski; Yann LeCun (CoRR, 2014)

Spectral Networks and Locally Connected Networks on Graphs. - Joan Bruna; Wojciech Zaremba; Arthur Szlam; Yann LeCun (ICLR, 2014)

The Loss Surface of Multilayer Networks. - Anna Choromanska; Mikael Henaff; Michaël Mathieu; Gérard Ben Arous; Yann LeCun (CoRR, 2014)

Understanding Deep Architectures using a Recursive Convolutional Network. - David Eigen; Jason Tyler Rolfe; Rob Fergus; Yann LeCun (ICLR (Workshop Poster), 2014)

Fast Training of Convolutional Networks through FFTs. - Michaël Mathieu; Mikael Henaff; Yann LeCun (ICLR (Poster), 2014)

Fast Approximation of Rotations and Hessians matrices. - Michaël Mathieu; Yann LeCun (CoRR, 2014)

OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks. - Pierre Sermanet; David Eigen; Xiang Zhang 013; Michaël Mathieu; Rob Fergus; Yann LeCun (ICLR, 2014)

Convolutional nets and watershed cuts for real-time semantic Labeling of RGBD videos. - Camille Couprie; Clément Farabet; Laurent Najman; Yann LeCun (J. Mach. Learn. Res., 2014)

Real-Time Continuous Pose Recovery of Human Hands Using Convolutional Networks. - Jonathan Tompson; Murphy Stein; Yann LeCun; Ken Perlin (ACM Trans. Graph., 2014)

The Loss Surfaces of Multilayer Networks. - Anna Choromanska; Mikael Henaff; Michaël Mathieu; Gérard Ben Arous; Yann LeCun (AISTATS, 2015)

Open Problem: The landscape of the loss surfaces of multilayer networks. - Anna Choromanska; Yann LeCun; Gérard Ben Arous (COLT, 2015)

Efficient object localization using Convolutional Networks. - Jonathan Tompson; Ross Goroshin; Arjun Jain; Yann LeCun; Christoph Bregler (CVPR, 2015)

Computing the stereo matching cost with a convolutional neural network. - Jure Zbontar; Yann LeCun (CVPR, 2015)

Deep learning & convolutional networks. - Yann LeCun (Hot Chips Symposium, 2015)

Source separation with scattering Non-Negative Matrix Factorization. - Joan Bruna; Pablo Sprechmann; Yann LeCun (ICASSP, 2015)

Unsupervised Learning of Spatiotemporally Coherent Metrics. - Ross Goroshin; Joan Bruna; Jonathan Tompson; David Eigen; Yann LeCun (ICCV, 2015)

Learning to Linearize Under Uncertainty. - Ross Goroshin; Michaël Mathieu; Yann LeCun (NIPS, 2015)

Character-level Convolutional Networks for Text Classification. - Xiang Zhang 013; Junbo Jake Zhao; Yann LeCun (NIPS, 2015)

A theoretical argument for complex-valued convolutional networks. - Joan Bruna; Soumith Chintala; Yann LeCun; Serkan Piantino; Arthur Szlam; Mark Tygert (CoRR, 2015)

High Performance Computer Acoustic Data Accelerator: A New System for Exploring Marine Mammal Acoustics for Big Data Applications. - Peter Dugan; John Zollweg; Marian Popescu; Denise Risch; Hervé Glotin; Yann LeCun; Christopher W. Clark (CoRR, 2015)

Unsupervised Feature Learning from Temporal Data. - Ross Goroshin; Joan Bruna; Jonathan Tompson; David Eigen; Yann LeCun (ICLR (Workshop), 2015)

Deep Convolutional Networks on Graph-Structured Data. - Mikael Henaff; Joan Bruna; Yann LeCun (CoRR, 2015)

Explorations on high dimensional landscapes. - Levent Sagun; V. Ugur Güney; Yann LeCun (ICLR (Workshop), 2015)

Universality in halting time and its applications in optimization. - Levent Sagun; Thomas Trogdon; Yann LeCun (CoRR, 2015)

Audio Source Separation with Discriminative Scattering Networks. - Pablo Sprechmann; Joan Bruna; Yann LeCun (ICLR (Workshop), 2015)

Fast Convolutional Nets With fbfft: A GPU Performance Evaluation. - Nicolas Vasilache; Jeff Johnson; Michaël Mathieu; Soumith Chintala; Serkan Piantino; Yann LeCun (ICLR, 2015)

Deep learning with Elastic Averaging SGD. - Sixin Zhang; Anna Choromanska; Yann LeCun (ICLR (Workshop), 2015)

Text Understanding from Scratch. - Xiang Zhang 013; Yann LeCun (CoRR, 2015)

Stacked What-Where Auto-encoders. - Junbo Jake Zhao; Michaël Mathieu; Ross Goroshin; Yann LeCun (CoRR, 2015)

Guest Editorial: Deep Learning. - Marc'Aurelio Ranzato; Geoffrey E. Hinton; Yann LeCun (Int. J. Comput. Vis., 2015)

Deep learning. - Yann LeCun; Yoshua Bengio; Geoffrey E. Hinton (Nat., 2015)

Very deep multilingual convolutional neural networks for LVCSR. - Tom Sercu; Christian Puhrsch; Brian Kingsbury; Yann LeCun (ICASSP, 2016)

Binary embeddings with structured hashed projections. - Anna Choromanska; Krzysztof Choromanski; Mariusz Bojarski; Tony Jebara; Sanjiv Kumar; Yann LeCun (ICML, 2016)

Recurrent Orthogonal Networks and Long-Memory Tasks. - Mikael Henaff; Arthur Szlam; Yann LeCun (ICML, 2016)

Disentangling factors of variation in deep representation using adversarial training. - Michaël Mathieu; Junbo Jake Zhao; Pablo Sprechmann; Aditya Ramesh; Yann LeCun (NIPS, 2016)

Super-Resolution with Deep Convolutional Sufficient Statistics. - Joan Bruna; Pablo Sprechmann; Yann LeCun (ICLR (Poster), 2016)

Very Deep Convolutional Networks for Natural Language Processing. - Alexis Conneau; Holger Schwenk; Loïc Barrault; Yann LeCun (CoRR, 2016)

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. - Peter J. Dugan; Christopher W. Clark; Yann André LeCun; Sofie M. Van Parijs (CoRR, 2016)

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. - Peter J. Dugan; Christopher W. Clark; Yann André LeCun; Sofie M. Van Parijs (CoRR, 2016)

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. - Peter J. Dugan; Christopher W. Clark; Yann André LeCun; Sofie M. Van Parijs (CoRR, 2016)

Phase 3: DCL System Using Deep Learning Approaches for Land-based or Ship-based Real-Time Recognition and Localization of Marine Mammals - Bioacoustic Applicaitons. - Peter J. Dugan; Christopher W. Clark; Yann André LeCun; Sofie M. Van Parijs (CoRR, 2016)

Orthogonal RNNs and Long-Memory Tasks. - Mikael Henaff; Arthur Szlam; Yann LeCun (CoRR, 2016)

What is the Best Feature Learning Procedure in Hierarchical Recognition Architectures? - Kevin Jarrett; Koray Kavukcuoglu; Karol Gregor; Yann LeCun (CoRR, 2016)

Simultaneous Learning of Trees and Representations for Extreme Classification, with Application to Language Modeling. - Yacine Jernite; Anna Choromanska; David A. Sontag; Yann LeCun (CoRR, 2016)

Deep multi-scale video prediction beyond mean square error. - Michaël Mathieu; Camille Couprie; Yann LeCun (ICLR (Poster), 2016)

Disentangling factors of variation in deep representations using adversarial training. - Michaël Mathieu; Junbo Jake Zhao; Pablo Sprechmann; Aditya Ramesh; Yann LeCun (CoRR, 2016)

Fast Incremental Learning for Off-Road Robot Navigation. - Artem Provodin; Liila Torabi; Beat Flepp; Yann LeCun; Michael Sergio; Lawrence D. Jackel; Urs Muller; Jure Zbontar (CoRR, 2016)

Singularity of the Hessian in Deep Learning. - Levent Sagun; Léon Bottou; Yann LeCun (CoRR, 2016)

Energy-based Generative Adversarial Network. - Junbo Jake Zhao; Michaël Mathieu; Yann LeCun (CoRR, 2016)

Stereo Matching by Training a Convolutional Neural Network to Compare Image Patches. - Jure Zbontar; Yann LeCun (J. Mach. Learn. Res., 2016)

A Mathematical Motivation for Complex-Valued Convolutional Networks. - Mark Tygert; Joan Bruna; Soumith Chintala; Yann LeCun; Serkan Piantino; Arthur Szlam (Neural Comput., 2016)

Universum Prescription: Regularization Using Unlabeled Data. - Xiang Zhang 013; Yann LeCun (AAAI, 2017)

Very Deep Convolutional Networks for Text Classification. - Alexis Conneau; Holger Schwenk; Loïc Barrault; Yann LeCun (EACL (1), 2017)

Predicting Deeper into the Future of Semantic Segmentation. - Pauline Luc; Natalia Neverova; Camille Couprie; Jakob Verbeek; Yann LeCun (ICCV, 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 (ICLR (Poster), 2017)

Tracking the World State with Recurrent Entity Networks. - Mikael Henaff; Jason Weston; Arthur Szlam; Antoine Bordes; Yann LeCun (ICLR (Poster), 2017)

Energy-based Generative Adversarial Networks. - Junbo Jake Zhao; Michaël Mathieu; Yann LeCun (ICLR (Poster), 2017)

Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNNs. - Li Jing 001; Yichen Shen 001; Tena Dubcek; John Peurifoy; Scott A. Skirlo; Yann LeCun; Max Tegmark; Marin Soljacic (ICML, 2017)

Model-Based Planning in Discrete Action Spaces. - Mikael Henaff; William F. Whitney; Yann LeCun (CoRR, 2017)

Adversarially Regularized Autoencoders for Generating Discrete Structures. - Junbo Jake Zhao; Yoon Kim; Kelly Zhang; Alexander M. Rush; Yann LeCun (CoRR, 2017)

Which Encoding is the Best for Text Classification in Chinese, English, Japanese and Korean? - Xiang Zhang 013; Yann LeCun (CoRR, 2017)

Hierarchical loss for classification. - Cinna Wu; Mark Tygert; Yann LeCun (CoRR, 2017)

Prediction Under Uncertainty with Error-Encoding Networks. - Mikael Henaff; Junbo Jake Zhao; Yann LeCun (CoRR, 2017)

Geometric Deep Learning: Going beyond Euclidean data. - Michael M. Bronstein; Joan Bruna; Yann LeCun; Arthur Szlam; Pierre Vandergheynst (IEEE Signal Process. Mag., 2017)

A Closer Look at Spatiotemporal Convolutions for Action Recognition. - Du Tran; Heng Wang; Lorenzo Torresani; Jamie Ray; Yann LeCun; Manohar Paluri (CVPR, 2018)

Predicting Future Instance Segmentation by Forecasting Convolutional Features. - Pauline Luc; Camille Couprie; Yann LeCun; Jakob Verbeek (ECCV (9), 2018)

DesIGN: Design Inspiration from Generative Networks. - Othman Sbai; Mohamed Elhoseiny; Antoine Bordes; Yann LeCun; Camille Couprie (ECCV Workshops (3), 2018)

Comparing Dynamics: Deep Neural Networks versus Glassy Systems. - Marco Baity-Jesi; Levent Sagun; Mario Geiger; Stefano Spigler; Gérard Ben Arous; Chiara Cammarota; Yann LeCun; Matthieu Wyart; Giulio Biroli (ICML, 2018)

Adversarially Regularized Autoencoders. - Junbo Jake Zhao; Yoon Kim; Kelly Zhang; Alexander M. Rush; Yann LeCun (ICML, 2018)

GLoMo: Unsupervised Learning of Transferable Relational Graphs. - Zhilin Yang 001; Junbo Jake Zhao; Bhuwan Dhingra; Kaiming He; William W. Cohen; Ruslan Salakhutdinov; Yann LeCun (NeurIPS, 2018)

Byte-Level Recursive Convolutional Auto-Encoder for Text. - Xiang Zhang 013; Yann LeCun (CoRR, 2018)

Predicting Future Instance Segmentations by Forecasting Convolutional Features. - Pauline Luc; Camille Couprie; Yann LeCun; Jakob Verbeek (CoRR, 2018)

Towards Understanding the Role of Over-Parametrization in Generalization of Neural Networks. - Behnam Neyshabur; Zhiyuan Li 005; Srinadh Bhojanapalli; Yann LeCun; Nathan Srebro (CoRR, 2018)

Backpropagation for Implicit Spectral Densities. - Aditya Ramesh; Yann LeCun (CoRR, 2018)

GLoMo: Unsupervisedly Learned Relational Graphs as Transferable Representations. - Zhilin Yang 001; Junbo Jake Zhao; Bhuwan Dhingra; Kaiming He; William W. Cohen; Ruslan Salakhutdinov; Yann LeCun (CoRR, 2018)

Adversarially-Trained Normalized Noisy-Feature Auto-Encoder for Text Generation. - Xiang Zhang 013; Yann LeCun (CoRR, 2018)

A Spectral Regularizer for Unsupervised Disentanglement. - Aditya Ramesh; Youngduck Choi; Yann LeCun (CoRR, 2018)

Unsupervised Image Matching and Object Discovery as Optimization. - Huy V. Vo; Francis R. Bach; Minsu Cho; Kai Han 001; Yann LeCun; Patrick Pérez; Jean Ponce (CVPR, 2019)

Model-Predictive Policy Learning with Uncertainty Regularization for Driving in Dense Traffic. - Mikael Henaff; Alfredo Canziani; Yann LeCun (ICLR (Poster), 2019)

The role of over-parametrization in generalization of neural networks. - Behnam Neyshabur; Zhiyuan Li 005; Srinadh Bhojanapalli; Yann LeCun; Nathan Srebro (ICLR (Poster), 2019)

Deep Learning Hardware: Past, Present, and Future. - Yann LeCun (ISSCC, 2019)

Learning about an exponential amount of conditional distributions. - Mohamed Ishmael Belghazi; Maxime Oquab; Yann LeCun; David Lopez-Paz (CoRR, 2019)

Inspirational Adversarial Image Generation. - Morgane Rivière; Olivier Teytaud; Jérémy Rapin; Yann LeCun; Camille Couprie (CoRR, 2019)

Implicit Rank-Minimizing Autoencoder. - Li Jing 001; Jure Zbontar; Yann LeCun (NeurIPS, 2020)

Transformer visualization via dictionary learning: contextualized embedding as a linear superposition of transformer factors. - Zeyu Yun; Yubei Chen; Bruno A. Olshausen; Yann LeCun (DeeLIO@NAACL-HLT, 2021)

MDETR - Modulated Detection for End-to-End Multi-Modal Understanding. - Aishwarya Kamath; Mannat Singh; Yann LeCun; Gabriel Synnaeve; Ishan Misra; Nicolas Carion (ICCV, 2021)

Barlow Twins: Self-Supervised Learning via Redundancy Reduction. - Jure Zbontar; Li Jing 001; Ishan Misra; Yann LeCun; Stéphane Deny (ICML, 2021)

Deep learning for AI. - Yoshua Bengio; Yann LeCun; Geoffrey E. Hinton (Commun. ACM, 2021)

Recurrent Parameter Generators. - Jiayun Wang; Yubei Chen; Stella X. Yu; Brian Cheung; Yann LeCun (CoRR, 2021)

Learning in High Dimension Always Amounts to Extrapolation. - Randall Balestriero; Jerome Pesenti; Yann LeCun (CoRR, 2021)

Inspirational Adversarial Image Generation. - Baptiste Rozière; Morgane Rivière; Olivier Teytaud; Jérémy Rapin; Yann LeCun; Camille Couprie (IEEE Trans. Image Process., 2021)

DBPedia. - Xiang Zhang 013; Junbo Zhao; Yann LeCun (IEEE DataPort, 2021)

Decoupled Contrastive Learning. - Chun-Hsiao Yeh; Cheng-Yao Hong; Yen-Chi Hsu; Tyng-Luh Liu; Yubei Chen; Yann LeCun (ECCV (26), 2022)

VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning. - Adrien Bardes; Jean Ponce; Yann LeCun (ICLR, 2022)

Understanding Dimensional Collapse in Contrastive Self-supervised Learning. - Li Jing 001; Pascal Vincent; Yann LeCun; Yuandong Tian (ICLR, 2022)

The Effects of Regularization and Data Augmentation are Class Dependent. - Randall Balestriero; Léon Bottou; Yann LeCun (NeurIPS, 2022)

Contrastive and Non-Contrastive Self-Supervised Learning Recover Global and Local Spectral Embedding Methods. - Randall Balestriero; Yann LeCun (NeurIPS, 2022)

A Data-Augmentation Is Worth A Thousand Samples: Analytical Moments And Sampling-Free Training. - Randall Balestriero; Ishan Misra; Yann LeCun (NeurIPS, 2022)

VICRegL: Self-Supervised Learning of Local Visual Features. - Adrien Bardes; Jean Ponce; 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 001; Ce Liu 001; Yann LeCun; Nanyun Peng 001; Jianfeng Gao 001; Lijuan Wang (NeurIPS, 2022)

projUNN: efficient method for training deep networks with unitary matrices. - Bobak Toussi Kiani; Randall Balestriero; Yann LeCun; Seth Lloyd (NeurIPS, 2022)

Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors. - Ravid Shwartz-Ziv; Micah Goldblum; Hossein Souri; Sanyam Kapoor; Chen Zhu 001; Yann LeCun; Andrew Gordon Wilson (NeurIPS, 2022)

Neural Manifold Clustering and Embedding. - Zengyi Li; Yubei Chen; Yann LeCun; Friedrich T. Sommer (CoRR, 2022)

A Data-Augmentation Is Worth A Thousand Samples: Exact Quantification From Analytical Augmented Sample Moments. - Randall Balestriero; Ishan Misra; Yann LeCun (CoRR, 2022)

Separating the World and Ego Models for Self-Driving. - Vlad Sobal; Alfredo Canziani; Nicolas Carion; Kyunghyun Cho; Yann LeCun (CoRR, 2022)

Masked Siamese ConvNets. - Li Jing 001; Jiachen Zhu 002; Yann LeCun (CoRR, 2022)

Intra-Instance VICReg: Bag of Self-Supervised Image Patch Embedding. - Yubei Chen; Adrien Bardes; Zengyi Li; Yann LeCun (CoRR, 2022)

TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning. - Jiachen Zhu 002; Rafael M. Moraes; Serkan Karakulak; Vlad Sobol; Alfredo Canziani; Yann LeCun (CoRR, 2022)

What Do We Maximize in Self-Supervised Learning? - Ravid Shwartz-Ziv; Randall Balestriero; Yann LeCun (CoRR, 2022)

Joint Embedding Self-Supervised Learning in the Kernel Regime. - Bobak Toussi Kiani; Randall Balestriero; Yubei Chen; Seth Lloyd; Yann LeCun (CoRR, 2022)

Variance Covariance Regularization Enforces Pairwise Independence in Self-Supervised Representations. - Grégoire Mialon; Randall Balestriero; Yann LeCun (CoRR, 2022)

Minimalistic Unsupervised Learning with the Sparse Manifold Transform. - Yubei Chen; Zeyu Yun; Yi Ma 001; Bruno A. Olshausen; Yann LeCun (CoRR, 2022)

Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution. - Anthony Zador; Blake A. Richards; Bence Ölveczky; Sean Escola; Yoshua Bengio; Kwabena Boahen 001; Matthew M. Botvinick; Dmitri B. Chklovskii; Anne Churchland; Claudia Clopath; James DiCarlo; Surya Ganguli; et al. (CoRR, 2022)

Unsupervised Learning of Structured Representations via Closed-Loop Transcription. - Shengbang Tong; Xili Dai; Yubei Chen; Mingyang Li; Zengyi Li; Brent Yi; Yann LeCun; Yi Ma 001 (CoRR, 2022)

Joint Embedding Predictive Architectures Focus on Slow Features. - Vlad Sobal; Jyothir S. V; Siddhartha Jalagam; Nicolas Carion; Kyunghyun Cho; Yann LeCun (CoRR, 2022)

Deep learning, reinforcement learning, and world models. - Yutaka Matsuo; Yann LeCun; Maneesh Sahani; Doina Precup; David Silver; Masashi Sugiyama; Eiji Uchibe; Jun Morimoto (Neural Networks, 2022)

Sparse Coding with Multi-layer Decoders using Variance Regularization. - Katrina Evtimova; Yann LeCun (Trans. Mach. Learn. Res., 2022)

Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture. - Mahmoud Assran; Quentin Duval; Ishan Misra; Piotr Bojanowski; Pascal Vincent; Michael G. Rabbat; Yann LeCun; Nicolas Ballas (CVPR, 2023)

Adapting Grounded Visual Question Answering Models to Low Resource Languages. - Ying Wang 063; Jonas Pfeiffer; Nicolas Carion; Yann LeCun; Aishwarya Kamath (CVPR Workshops, 2023)

Fast and Exact Enumeration of Deep Networks Partitions Regions. - Randall Balestriero; Yann LeCun (ICASSP, 2023)

Police: Provably Optimal Linear Constraint Enforcement For Deep Neural Networks. - Randall Balestriero; Yann LeCun (ICASSP, 2023)

Active Self-Supervised Learning: A Few Low-Cost Relationships Are All You Need. - Vivien Cabannes; Léon Bottou; Yann LeCun; Randall Balestriero (ICCV, 2023)

Minimalistic Unsupervised Representation Learning with the Sparse Manifold Transform. - Yubei Chen; Zeyu Yun; Yi Ma 001; Bruno A. 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 (ICLR, 2023)

The SSL Interplay: Augmentations, Inductive Bias, and Generalization. - Vivien Cabannes; Bobak Toussi Kiani; Randall Balestriero; Yann LeCun; Alberto Bietti (ICML, 2023)

RankMe: Assessing the Downstream Performance of Pretrained Self-Supervised Representations by Their Rank. - Quentin Garrido; Randall Balestriero; Laurent Najman; Yann LeCun (ICML, 2023)

Self-supervised learning of Split Invariant Equivariant representations. - Quentin Garrido; Laurent Najman; Yann LeCun (ICML, 2023)

A Generalization of ViT/MLP-Mixer to Graphs. - Xiaoxin He; Bryan Hooi; Thomas Laurent 001; Adam Perold; Yann LeCun; Xavier Bresson (ICML, 2023)

Reverse Engineering Self-Supervised Learning. - Ido Ben-Shaul; Ravid Shwartz-Ziv; Tomer Galanti; Shai Dekel; 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 T. Kiani (NeurIPS, 2023)

An Information Theory Perspective on Variance-Invariance-Covariance Regularization. - Ravid Shwartz-Ziv; Randall Balestriero; Kenji Kawaguchi; Tim G. J. Rudner; Yann LeCun (NeurIPS, 2023)

Compact and Optimal Deep Learning with Recurrent Parameter Generators. - Jiayun Wang; Yubei Chen; Stella X. Yu; Brian Cheung; Yann LeCun (WACV, 2023)

An Information-Theoretic Perspective on Variance-Invariance-Covariance Regularization. - Ravid Shwartz-Ziv; Randall Balestriero; Kenji Kawaguchi; Tim G. J. Rudner; Yann LeCun (CoRR, 2023)

EMP-SSL: Towards Self-Supervised Learning in One Training Epoch. - Shengbang Tong; Yubei Chen; Yi Ma 001; Yann LeCun (CoRR, 2023)

A Cookbook of Self-Supervised Learning. - 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; et al. (CoRR, 2023)

Introduction to Latent Variable Energy-Based Models: A Path Towards Autonomous Machine Intelligence. - Anna Dawid; Yann LeCun (CoRR, 2023)

Variance-Covariance Regularization Improves Representation Learning. - Jiachen Zhu 002; Ravid Shwartz-Ziv; Yubei Chen; Yann LeCun (CoRR, 2023)

MC-JEPA: A Joint-Embedding Predictive Architecture for Self-Supervised Learning of Motion and Content Features. - Adrien Bardes; Jean Ponce; Yann LeCun (CoRR, 2023)

Predicting masked tokens in stochastic locations improves masked image modeling. - Amir Bar; Florian Bordes; Assaf Shocher; Mahmoud Assran; Pascal Vincent; Nicolas Ballas; Trevor Darrell; Amir Globerson; Yann LeCun (CoRR, 2023)

URLOST: Unsupervised Representation Learning without Stationarity or Topology. - Zeyu Yun; Juexiao Zhang; Bruno A. Olshausen; Yann LeCun; Yubei Chen (CoRR, 2023)

GAIA: a benchmark for General AI Assistants. - Grégoire Mialon; Clémentine Fourrier; Craig Swift; Thomas Wolf 008; Yann LeCun; Thomas Scialom (CoRR, 2023)

Gradient-based Planning with World Models. - Jyothir S. V; Siddhartha Jalagam; Yann LeCun; Vlad Sobal (CoRR, 2023)

Bag of Image Patch Embedding Behind the Success of Self-Supervised Learning. - Yubei Chen; Adrien Bardes; Zengyi Li; Yann LeCun (Trans. Mach. Learn. Res., 2023)

Augmented Language Models: a Survey. - 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; et al. (Trans. Mach. Learn. Res., 2023)

VoLTA: Vision-Language Transformer with Weakly-Supervised Local-Feature Alignment. - Shraman Pramanick; Li Jing 001; Sayan Nag; Jiachen Zhu 002; Hardik Shah; Yann LeCun; Rama Chellappa (Trans. Mach. Learn. Res., 2023)

Language, common sense, and the Winograd schema challenge. - Jacob Browning; Yann LeCun (Artif. Intell., 2023)

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 001 (CPAL, 2024)

Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs. - Shengbang Tong; Zhuang Liu 003; Yuexiang Zhai; Yi Ma 001; Yann LeCun; Saining Xie (CVPR, 2024)

EgoPet: Egomotion and Interaction Data from an Animal's Perspective. - Amir Bar; Arya Bakhtiar; Danny Tran; Antonio Loquercio; Jathushan Rajasegaran; Yann LeCun; Amir Globerson; Trevor Darrell (ECCV (37), 2024)

Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning. - Xiaoxin He; Xavier Bresson; Thomas Laurent 001; Adam Perold; Yann LeCun; Bryan Hooi (ICLR, 2024)

GAIA: a benchmark for General AI Assistants. - Grégoire Mialon; Clémentine Fourrier; Thomas Wolf 008; Yann LeCun; Thomas Scialom (ICLR, 2024)

How Learning by Reconstruction Produces Uninformative Features For Perception. - Randall Balestriero; Yann LeCun (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 (ICML, 2024)

The Entropy Enigma: Success and Failure of Entropy Minimization. - Ori Press; Ravid Shwartz-Ziv; Yann LeCun; Matthias Bethge (ICML, 2024)

G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering. - Xiaoxin He; Yijun Tian 001; Yifei Sun 002; Nitesh V. Chawla; Thomas Laurent 001; Yann LeCun; Xavier Bresson; Bryan Hooi (NeurIPS, 2024)

Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs. - 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; et al. (NeurIPS, 2024)

Fine-Tuning Large Vision-Language Models as Decision-Making Agents via Reinforcement Learning. - Simon Zhai; Hao Bai; Zipeng Lin; Jiayi Pan; Peter Tong; Yifei Zhou; Alane Suhr; Saining Xie; Yann LeCun; Yi Ma 001; Sergey Levine (NeurIPS, 2024)

Light-weight Probing of Unsupervised Representations for Reinforcement Learning. - Wancong Zhang; Anthony GX-Chen; Vlad Sobal; Yann LeCun; Nicolas Carion (RLJ, 2024)

Learning by Reconstruction Produces Uninformative Features For Perception. - Randall Balestriero; Yann LeCun (CoRR, 2024)

Learning and Leveraging World Models in Visual Representation Learning. - Quentin Garrido; Mahmoud Assran; Nicolas Ballas; Adrien Bardes; Laurent Najman; Yann LeCun (CoRR, 2024)

Advancing human-centric AI for robust X-ray analysis through holistic self-supervised learning. - Théo Moutakanni; Piotr Bojanowski; Guillaume Chassagnon; Céline Hudelot; Armand Joulin; Yann LeCun; Matthew J. Muckley; Maxime Oquab; Marie-Pierre Revel; Maria Vakalopoulou (CoRR, 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 001; Sergey Levine (CoRR, 2024)

Towards a Framework for Openness in Foundation Models: Proceedings from the Columbia Convening on Openness in Artificial Intelligence. - 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 001; et al. (CoRR, 2024)

Towards an Improved Understanding and Utilization of Maximum Manifold Capacity Representations. - 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; et al. (CoRR, 2024)

Just How Flexible are Neural Networks in Practice? - Ravid Shwartz-Ziv; Micah Goldblum; Arpit Bansal; C. Bayan Bruss; Yann LeCun; Andrew Gordon Wilson (CoRR, 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; et al. (CoRR, 2024)

LiveBench: A Challenging, Contamination-Free LLM Benchmark. - Colin White; Samuel Dooley; Manley Roberts; Arka Pal; Benjamin Feuer; Siddhartha Jain 001; Ravid Shwartz-Ziv; Neel Jain; Khalid Saifullah; Siddartha Naidu; Chinmay Hegde; Yann LeCun; et al. (CoRR, 2024)

PooDLe: Pooled and dense self-supervised learning from naturalistic videos. - Alex N. Wang; Christopher Hoang; Yuwen Xiong; Yann LeCun; Mengye Ren (CoRR, 2024)

Multi-modal AI for comprehensive breast cancer prognostication. - 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; et al. (CoRR, 2024)

DINO-WM: World Models on Pre-trained Visual Features enable Zero-shot Planning. - Gaoyue Zhou; Hengkai Pan; Yann LeCun; Lerrel Pinto (CoRR, 2024)

Does Representation Matter? Exploring Intermediate Layers in Large Language Models. - Oscar Skean; Md Rifat Arefin; Yann LeCun; Ravid Shwartz-Ziv (CoRR, 2024)

Video Representation Learning with Joint-Embedding Predictive Architectures. - Katrina Drozdov; Ravid Shwartz-Ziv; Yann LeCun (CoRR, 2024)

MetaMorph: Multimodal Understanding and Generation via Instruction Tuning. - Shengbang Tong; David Fan; Jiachen Zhu 002; Yunyang Xiong; Xinlei Chen; Koustuv Sinha; Michael Rabbat; Yann LeCun; Saining Xie; Zhuang Liu 003 (CoRR, 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 (Trans. Mach. Learn. Res., 2024)

Blockwise Self-Supervised Learning at Scale. - Shoaib Ahmed Siddiqui; David Krueger 001; Yann LeCun; Stéphane Deny (Trans. Mach. Learn. Res., 2024)

To Compress or Not to Compress - Self-Supervised Learning and Information Theory: A Review. - Ravid Shwartz-Ziv; Yann LeCun (Entropy, 2024)

Editorial: Learning With Fewer Labels in Computer Vision. - Li Liu 002; Timothy M. Hospedales; Yann LeCun; Mingsheng Long; Jiebo Luo 001; Wanli Ouyang; Matti Pietikäinen; Tinne Tuytelaars (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Forgotten Polygons: Multimodal Large Language Models are Shape-Blind. - William Rudman; Michal Golovanevsky; Amir Bar; Vedant Palit; Yann LeCun; Carsten Eickhoff; Ritambhara Singh (ACL (Findings), 2025)

Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization. - Deep Chakraborty; Yann LeCun; Tim G. J. Rudner; Erik G. Learned-Miller (AISTATS, 2025)

Transformers without Normalization. - Jiachen Zhu 002; Xinlei Chen; Kaiming He; Yann LeCun; Zhuang Liu 003 (CVPR, 2025)

Navigation World Models. - Amir Bar; Gaoyue Zhou; Danny Tran; Trevor Darrell; Yann LeCun (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 (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)

Hierarchical World Models as Visual Whole-Body Humanoid Controllers. - Nicklas Hansen 001; Jyothir S. V; Vlad Sobal; Yann LeCun; Xiaolong Wang 004; Hao Su 001 (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 (ICLR, 2025)

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 (ICLR, 2025)

PooDLe🐩: Pooled and dense self-supervised learning from naturalistic videos. - Alex N. Wang; Christopher Hoang; Yuwen Xiong; Yann LeCun; Mengye Ren (ICLR, 2025)

LiveBench: A Challenging, Contamination-Limited LLM Benchmark. - Colin White; Samuel Dooley; Manley Roberts; Arka Pal; Benjamin Feuer; Siddhartha Jain 001; Ravid Shwartz-Ziv; Neel Jain; Khalid Saifullah; Sreemanti Dey; Shubh-Agrawal; Sandeep Singh Sandha; et al. (ICLR, 2025)

URLOST: Unsupervised Representation Learning without Stationarity or Topology. - Zeyu Yun; Juexiao Zhang; Yann LeCun; Yubei Chen (ICLR, 2025)

Layer by Layer: Uncovering Hidden Representations in Language Models. - Oscar Skean; Md Rifat Arefin; Dan Zhao; Niket Patel; Jalal Naghiyev; Yann LeCun; Ravid Shwartz-Ziv (CoRR, 2025)

Intuitive physics understanding emerges from self-supervised pretraining on natural videos. - Quentin Garrido; Nicolas Ballas; Mahmoud Assran; Adrien Bardes; Laurent Najman; Michael Rabbat; Emmanuel Dupoux; Yann LeCun (CoRR, 2025)

Learning from Reward-Free Offline Data: A Case for Planning with Latent Dynamics Models. - Vlad Sobal; Wancong Zhang; Kynghyun Cho; Randall Balestriero; Tim G. J. Rudner; Yann LeCun (CoRR, 2025)

Forgotten Polygons: Multimodal Large Language Models are Shape-Blind. - William Rudman; Michal Golovanesky; Amir Bar; Vedant Palit; Yann LeCun; Carsten Eickhoff; Ritambhara Singh (CoRR, 2025)

Scaling Language-Free Visual Representation Learning. - David Fan; Shengbang Tong; Jiachen Zhu 002; Koustuv Sinha; Zhuang Liu 003; Xinlei Chen; Michael Rabbat; Nicolas Ballas; Yann LeCun; Amir Bar; Saining Xie (CoRR, 2025)

From Tokens to Thoughts: How LLMs and Humans Trade Compression for Meaning. - Chen Shani; Dan Jurafsky; Yann LeCun; Ravid Shwartz-Ziv (CoRR, 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 (CoRR, 2025)

V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning. - 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; et al. (CoRR, 2025)

Whole-Body Conditioned Egocentric Video Prediction. - Yutong Bai; Danny Tran; Amir Bar; Yann LeCun; Trevor Darrell; Jitendra Malik (CoRR, 2025)

Back to the Features: DINO as a Foundation for Video World Models. - Federico Baldassarre; Marc Szafraniec; Basile Terver; Vasil Khalidov; Francisco Massa; Yann LeCun; Patrick Labatut; Maximilian Seitzer; Piotr Bojanowski (CoRR, 2025)