Yann LeCun

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Signature Verification Using A "Siamese" Time Delay Neural Network

Yann LeCun, Isabelle Guyon, Eduard Säckinger, 1993, Int. J. Pattern Recognit. Artif. Intell..

Yann LeCun, Raia Hadsell, Sumit Chopra, 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

The mnist database of handwritten digits

Yann LeCun, Corinna Cortes, 2005 .

Generalization and network design strategies

Yann LeCun, Yann LeCun, 1989 .

A time delay neural network character recognizer for a touch terminal

Isabelle Guyon, Yann LeCun, Yann LeCun, 1990 .

Gradient-based learning applied to document recognition

Yoshua Bengio, Yann LeCun, Léon Bottou, 1998, Proc. IEEE.

No more pesky learning rates pdf

Tom Schaul, Yann LeCun, Sixin Zhang, 2012, ICML.

Learning methods for generic object recognition with invariance to pose and lighting

Y. LeCun, Fu Jie Huang, L. Bottou, 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

Efficient BackProp

Klaus-Robert Müller, Yann LeCun, Léon Bottou, 2012, Neural Networks: Tricks of the Trade.

Scaling learning algorithms towards AI

Yoshua Bengio, Yann LeCun, Yoshua Bengio, 2007 .

Backpropagation Applied to Handwritten Zip Code Recognition

Lawrence D. Jackel, Yann LeCun, Bernhard E. Boser, 1989, Neural Computation.

Improving the convergence of back-propagation learning with second-order methods

Yann LeCun, Suzanna Becker, Yann LeCun, 1989 .

Handwritten Digit Recognition with a Back-Propagation Network

Lawrence D. Jackel, Yann LeCun, Bernhard E. Boser, 1989, NIPS.

Comparison of classifier methods: a case study in handwritten digit recognition

Isabelle Guyon, Harris Drucker, Yann LeCun, 1994, Proceedings of the 12th IAPR International Conference on Pattern Recognition, Vol. 3 - Conference C: Signal Processing (Cat. No.94CH3440-5).

Efficient Pattern Recognition Using a New Transformation Distance

Yann LeCun, Patrice Y. Simard, John S. Denker, 1992, NIPS.

Une procedure d'apprentissage pour reseau a seuil asymmetrique (A learning scheme for asymmetric threshold networks)

Yann LeCun, Yann LeCun, 1985 .

Tangent Prop - A Formalism for Specifying Selected Invariances in an Adaptive Network

Yann LeCun, Patrice Y. Simard, John S. Denker, 1991, NIPS.

Optimal Brain Damage

Yann LeCun, Sara A. Solla, John S. Denker, 1989, NIPS.

Transformation Invariance in Pattern Recognition-Tangent Distance and Tangent Propagation

Yann LeCun, Patrice Y. Simard, John S. Denker, 1996, Neural Networks: Tricks of the Trade.

Sn: A simulator for connectionist models

Léon Bottou, Yann LeCun, L. Bottou, 1988 .

Learning algorithms for classification: A comparison on handwritten digit recognition

Harris Drucker, Lawrence D. Jackel, Patrice Y. Simard, 1995 .

Comparison of learning algorithms for handwritten digit recognition

Harris Drucker, Lawrence D. Jackel, Patrice Y. Simard, 1995 .

Transforming Neural-Net Output Levels to Probability Distributions

Yann LeCun, John S. Denker, Yann LeCun, 1990, NIPS.

A neural network approach to handprint character recognition

Lawrence D. Jackel, Yann LeCun, Edwin P. D. Pednault, 1991, COMPCON Spring '91 Digest of Papers.

Handwritten zip code recognition with multilayer networks

Yann LeCun, Henry S. Baird, Richard E. Howard, 1990, [1990] Proceedings. 10th International Conference on Pattern Recognition.

Model-Based Planning with Discrete and Continuous Actions

Yann LeCun, Mikael Henaff, William F. Whitney, 2017 .

Handwritten Digit Recognition: Applications of Neural Net Chips and Automatic Learning

Isabelle Guyon, Yann LeCun, Isabelle Guyon, 1989, NATO Neurocomputing.

Design of a neural network character recognizer for a touch terminal

Isabelle Guyon, Yann LeCun, John S. Denker, 1991, Pattern Recognit..

Constrained neural network for unconstrained handwritten digit recognition

Lawrence D. Jackel, Henry S. Baird, Yann LeCun, 1990 .

Handwritten character recognition using neural network architectures

Lawrence D. Jackel, Yann LeCun, Ofer Matan, 1990 .

Large Scale Online Learning

Yann LeCun, Léon Bottou, L. Bottou, 2003, NIPS.

Writer independent and writer adaptive neural network for on-line character recognition

Yann LeCun, Isabelle Guyon, P. Albrecht, 1992 .

An efficient algorithm for learning invariance in adaptive classifiers

Patrice Y. Simard, Bernard Victorri, Y. Le Cun, 1992, Proceedings., 11th IAPR International Conference on Pattern Recognition. Vol.II. Conference B: Pattern Recognition Methodology and Systems.

Reading handwritten digits: a ZIP code recognition system

Lawrence D. Jackel, Yann LeCun, Edwin P. D. Pednault, 1992, Computer.

Application of the ANNA neural network chip to high-speed character recognition

Lawrence D. Jackel, Yann LeCun, Bernhard E. Boser, 1992, IEEE Trans. Neural Networks.

Multi-Digit Recognition Using a Space Displacement Neural Network

Yann LeCun, Christopher J. C. Burges, Ofer Matan, 1991, NIPS.

Hardware requirements for neural network pattern classifiers: a case study and implementation

Lawrence D. Jackel, Yann LeCun, Bernhard E. Boser, 1992, IEEE Micro.

Handwritten digit recognition: applications of neural network chips and automatic learning

I. Guyon, Y. Le Cun, L.D. Jackel, 1989, IEEE Communications Magazine.

Neural Network Applications in Character Recognition and Document Analysis

Lawrence D. Jackel, Yann LeCun, Jan Ben, 1994 .

Natural Versus "universal" Probability, Complexity, And Entropy

J.S. Denker, Y. leCun, Yann LeCun, 1992, Workshop on Physics and Computation.

Efficient Learning of Sparse Representations with an Energy-Based Model

Marc'Aurelio Ranzato, Yann LeCun, Christopher S. Poultney, 2006, NIPS.

Boosting and Other Ensemble Methods

Harris Drucker, Lawrence D. Jackel, Yann LeCun, 1994, Neural Computation.

Gradient-based Learning Applied to Document Recognition Gt Graph Transformer. Gtn Graph Transformer Network. Hmm Hidden Markov Model. Hos Heuristic Oversegmentation. K-nn K-nearest Neighbor. Nn Neural Network. Ocr Optical Character Recognition. Pca Principal Component Analysis. Rbf Radial Basis Func

Yoshua Bengio, L. Bottou, Yann LeCun, 1998 .

NeuFlow: A runtime reconfigurable dataflow processor for vision

Berin Martini, Eugenio Culurciello, Yann LeCun, 2011, CVPR 2011 WORKSHOPS.

Emergence of Complex-Like Cells in a Temporal Product Network with Local Receptive Fields pdf

Yann LeCun, Karol Gregor, Yann LeCun, 2010, ArXiv.

Toward automatic phenotyping of developing embryos from videos

Yann LeCun, Léon Bottou, Paolo Emilio Barbano, 2005, IEEE Transactions on Image Processing.

Regularization of Neural Networks using DropConnect

Yann LeCun, Li Wan, Rob Fergus, 2013, ICML.

Learning Hierarchical Features for Scene Labeling

Camille Couprie, Clément Farabet, Laurent Najman, 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Backpropagation for Implicit Spectral Densities pdf

Yann LeCun, Aditya Ramesh, Yann LeCun, 2018, ArXiv.

Improving generalization performance using double backpropagation

Harris Drucker, Yann LeCun, Yann LeCun, 1992, IEEE Trans. Neural Networks.

Convolutional networks and applications in vision

Yann LeCun, Clément Farabet, Koray Kavukcuoglu, 2010, Proceedings of 2010 IEEE International Symposium on Circuits and Systems.

Pedestrian Detection with Unsupervised Multi-stage Feature Learning

Yann LeCun, Koray Kavukcuoglu, Pierre Sermanet, 2012, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

Convolutional neural networks applied to house numbers digit classification

Yann LeCun, Pierre Sermanet, Soumith Chintala, 2012, Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012).

Deep learning with Elastic Averaging SGD

Yann LeCun, Anna Choromanska, Sixin Zhang, 2014, NIPS.

Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation

Joan Bruna, Yann LeCun, Wojciech Zaremba, 2014, NIPS.

Boxlets: A Fast Convolution Algorithm for Signal Processing and Neural Networks

Yann LeCun, Patrice Y. Simard, Léon Bottou, 1998, NIPS.

Learning Convolutional Feature Hierarchies for Visual Recognition

Y-Lan Boureau, Yann LeCun, Koray Kavukcuoglu, 2010, NIPS.

Object Recognition with Gradient-Based Learning

Yoshua Bengio, Yann LeCun, Léon Bottou, 1999, Shape, Contour and Grouping in Computer Vision.

Explorations on high dimensional landscapes pdf

Yann LeCun, Levent Sagun, V. Ugur Güney, 2014, ICLR.

LeRec: A NN/HMM Hybrid for On-Line Handwriting Recognition

Yoshua Bengio, Yann LeCun, Christopher J. C. Burges, 1995, Neural Computation.

A Unified Energy-Based Framework for Unsupervised Learning

Marc'Aurelio Ranzato, Y-Lan Boureau, Yann LeCun, 2007, AISTATS.

A theoretical framework for back-propagation

Yann LeCun, Yann LeCun, 1988 .

Convolutional networks for images, speech, and time series

Yoshua Bengio, Yann LeCun, Yoshua Bengio, 1998 .

The Loss Surfaces of Multilayer Networks

Yann LeCun, Anna Choromanska, Mikael Henaff, 2014, AISTATS.

Sparse Feature Learning for Deep Belief Networks

Marc'Aurelio Ranzato, Y-Lan Boureau, Yann LeCun, 2007, NIPS.

Synergistic Face Detection and Pose Estimation with Energy-Based Models

Yann LeCun, Margarita Osadchy, Matthew L. Miller, 2004, J. Mach. Learn. Res..

Measuring the VC-Dimension of a Learning Machine

Yann LeCun, Vladimir Vapnik, Esther Levin, 1994, Neural Computation.

Learning long‐range vision for autonomous off‐road driving

Yann LeCun, Raia Hadsell, Koray Kavukcuoglu, 2009, J. Field Robotics.

Deep belief net learning in a long-range vision system for autonomous off-road driving

Yann LeCun, Raia Hadsell, Pierre Sermanet, 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Fast Inference in Sparse Coding Algorithms with Applications to Object Recognition pdf

Marc'Aurelio Ranzato, Yann LeCun, Koray Kavukcuoglu, 2010, ArXiv.

Entropy-SGD: biasing gradient descent into wide valleys pdf

Stefano Soatto, Yann LeCun, Christian Borgs, 2016, ICLR.

Pattern Recognition and Neural Networks

Yoshua Bengio, Yann LeCun, Yoshua Bengio, 1995 .

Traffic sign recognition with multi-scale Convolutional Networks

Yann LeCun, Pierre Sermanet, Pierre Sermanet, 2011, The 2011 International Joint Conference on Neural Networks.

Fast Training of Convolutional Networks through FFTs pdf

Yann LeCun, Mikael Henaff, Michaël Mathieu, 2013, ICLR.

Dimensionality Reduction by Learning an Invariant Mapping

Yann LeCun, Raia Hadsell, Sumit Chopra, 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

Unsupervised Learning of Invariant Feature Hierarchies with Applications to Object Recognition

Marc'Aurelio Ranzato, Y-Lan Boureau, Yann LeCun, 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

Fast Convolutional Nets With fbfft: A GPU Performance Evaluation pdf

Jeff Johnson, Yann LeCun, Nicolas Vasilache, 2014, ICLR.

Deep multi-scale video prediction beyond mean square error pdf

Yann LeCun, Camille Couprie, Michaël Mathieu, 2015, ICLR.

Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNNs pdf

Yann LeCun, Li Jing, Max Tegmark, 2016, ICML.

Learning processes in an asymmetric threshold network

Yann LeCun, Yann LeCun, 1986 .

Understanding Deep Architectures using a Recursive Convolutional Network pdf

Yann LeCun, Rob Fergus, David Eigen, 2013, ICLR.

Joint Training of a Convolutional Network and a Graphical Model for Human Pose Estimation

Jonathan Tompson, Yann LeCun, Christoph Bregler, 2014, NIPS.

Convolutional Learning of Spatio-temporal Features

Yann LeCun, Christoph Bregler, Graham W. Taylor, 2010, ECCV.

Off-Road Obstacle Avoidance through End-to-End Learning

Yann LeCun, Beat Flepp, Jan Ben, 2005, NIPS.

A multirange architecture for collision‐free off‐road robot navigation

Yann LeCun, Raia Hadsell, Pierre Sermanet, 2009, J. Field Robotics.

Classification of patterns of EEG synchronization for seizure prediction

Yann LeCun, P. Mirowski, D. Madhavan, 2009, Clinical Neurophysiology.

The Loss Surface of Multilayer Networks pdf

Yann LeCun, Anna Choromanska, Mikael Henaff, 2014, ArXiv.

Large-scale Learning with SVM and Convolutional for Generic Object Categorization

Yann LeCun, Fu Jie Huang, F. Huang, 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

Stacked What-Where Auto-encoders pdf

Yann LeCun, Junbo Jake Zhao, Michaël Mathieu, 2015, ArXiv.

Loss Functions for Discriminative Training of Energy-Based Models

Yann LeCun, Fu Jie Huang, F. Huang, 2005, AISTATS.

Deep Learning Made Easier by Linear Transformations in Perceptrons

Tapani Raiko, Harri Valpola, Yann LeCun, 2012, AISTATS.

The Boosting Approach to Machine Learning An Overview

Harris Drucker, Lawrence D. Jackel, Yann LeCun, 2003 .

Energy-based Generative Adversarial Network pdf

Yann LeCun, Junbo Jake Zhao, Michaël Mathieu, 2016, ICLR.

Learning long-range vision for autonomous off-road driving

Urs A. Muller, Yann LeCun, Raia Hadsell, 2009 .

A Theoretical Analysis of Feature Pooling in Visual Recognition

Jean Ponce, Y-Lan Boureau, Yann LeCun, 2010, ICML.

Learning mid-level features for recognition

Jean Ponce, Y-Lan Boureau, Yann LeCun, 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

Word normalization for on-line handwritten word recognition

Yoshua Bengio, Yann LeCun, Yoshua Bengio, 1994 .

Energy-Based Models in Document Recognition and Computer Vision

Marc'Aurelio Ranzato, Yann LeCun, Sumit Chopra, 2007 .

SPEED-RANGE DILEMMAS FOR VISION-BASED NAVIGATION IN UNSTRUCTURED TERRAIN

Urs A. Muller, Yann LeCun, Beat Flepp, 2007 .

Energy-Based Models in Document Recognition and Computer Vision

Marc'Aurelio Ranzato, Yann LeCun, Sumit Chopra, 2007, Ninth International Conference on Document Analysis and Recognition (ICDAR 2007).

Reverse TDNN: An Architecture For Trajectory Generation

Yann LeCun, Patrice Y. Simard, Yann LeCun, 1991, NIPS.

An FPGA-based stream processor for embedded real-time vision with Convolutional Networks

Yann LeCun, Clément Farabet, Cyril Poulet, 2009, 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops.

Open Problem: The landscape of the loss surfaces of multilayer networks

Yann LeCun, Anna Choromanska, Gérard Ben Arous, 2015, COLT.

The Need for Open Source Software in Machine Learning

Carl E. Rasmussen, Gunnar Rätsch, Bernhard Schölkopf, 2007, J. Mach. Learn. Res..

Super-Resolution with Deep Convolutional Sufficient Statistics pdf

Joan Bruna, Yann LeCun, Pablo Sprechmann, 2015, ICLR.

Geometric Deep Learning: Going beyond Euclidean data

Pierre Vandergheynst, Joan Bruna, Yann LeCun, 2016, IEEE Signal Process. Mag..

A multirange architecture for collision-free off-road robot navigation

Yann LeCun, Raia Hadsell, Pierre Sermanet, 2009 .

Learning Fast Approximations of Sparse Coding

Yann LeCun, Karol Gregor, Yann LeCun, 2010, ICML.

EBLearn: Open-Source Energy-Based Learning in C++

Yann LeCun, Koray Kavukcuoglu, Pierre Sermanet, 2009, 2009 21st IEEE International Conference on Tools with Artificial Intelligence.

Signal recovery from Pooling Representations

Joan Bruna, Yann LeCun, Arthur Szlam, 2013, ICML.

Towards Understanding the Role of Over-Parametrization in Generalization of Neural Networks pdf

Yann LeCun, Zhiyuan Li, Nathan Srebro, 2018, ArXiv.

Dynamic auto-encoders for semantic indexing

Marc'Aurelio Ranzato, Yann LeCun, Piotr Mirowski, 2010 .

Globally trained handwritten word recognizer using spatial representation, space displacement neural networks and hidden Markov models

Yoshua Bengio, Yann LeCun, D. Henderson, 1993 .

Learning invariant features through topographic filter maps

Marc'Aurelio Ranzato, Yann LeCun, Koray Kavukcuoglu, 2009, CVPR.

Efficient object localization using Convolutional Networks

Jonathan Tompson, Yann LeCun, Ross Goroshin, 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Very Deep Convolutional Networks for Natural Language Processing pdf

Yann LeCun, Holger Schwenk, Loïc Barrault, 2016, ArXiv.

Orthogonal RNNs and Long-Memory Tasks pdf

Yann LeCun, Arthur Szlam, Mikael Henaff, 2016, ArXiv.

On the application of multimedia processing to telecommunications

Behzad Shahraray, Yann LeCun, Lawrence R. Rabiner, 1997, Proceedings of International Conference on Image Processing.

Efficient conversion of digital documents to multilayer raster formats

Yann LeCun, Léon Bottou, Patrick Haffner, 2001, Proceedings of Sixth International Conference on Document Analysis and Recognition.

1.1 Deep Learning Hardware: Past, Present, and Future

Yann LeCun, Yann LeCun, 2019, 2019 IEEE International Solid- State Circuits Conference - (ISSCC).

Time Series Modeling with Hidden Variables and Gradient-Based Algorithms

Yann LeCun, Piotr Mirowski, Yann LeCun, 2010 .

Saturating Auto-Encoder pdf

Yann LeCun, Ross Goroshin, Yann LeCun, 2013, ICLR.

The Power and Limits of Deep Learning

Yann LeCun, Yann LeCun, 2018, Research-Technology Management.

DjVu: a Compression Method for Distributing Scanned Documents in Color over the Internet

Yann LeCun, Léon Bottou, Patrick Haffner, 1998, Color Imaging Conference.

Unsupervised Image Matching and Object Discovery as Optimization

Patrick Pérez, Jean Ponce, Kai Han, 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

A theoretical argument for complex-valued convolutional networks pdf

Mark Tygert, Joan Bruna, Yann LeCun, 2015, ArXiv.

A Closer Look at Spatiotemporal Convolutions for Action Recognition

Yann LeCun, Lorenzo Torresani, Heng Wang, 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Djvu: Un systeme de compression d'images pour la distribution reticulaire de documents numerises (Djvu: An image compression system for distributing scanned document on the internet)

Yann LeCun, Léon Bottou, Patrick Haffner, 2000 .

DeSIGN: Design Inspiration from Generative Networks pdf

Yann LeCun, Camille Couprie, Antoine Bordes, 2018, ECCV Workshops.

Inspirational Adversarial Image Generation pdf

Olivier Teytaud, Yann LeCun, Camille Couprie, 2019, IEEE Transactions on Image Processing.

MoDeep: A Deep Learning Framework Using Motion Features for Human Pose Estimation

Jonathan Tompson, Yann LeCun, Christoph Bregler, 2014, ACCV.

Scene parsing with Multiscale Feature Learning, Purity Trees, and Optimal Covers pdf

Yann LeCun, Camille Couprie, Clément Farabet, 2012, ICML.

Character-level Convolutional Networks for Text Classification

Xiang Zhang, Yann LeCun, Junbo Jake Zhao, 2015, NIPS.

Hardware accelerated convolutional neural networks for synthetic vision systems

Berin Martini, Eugenio Culurciello, Yann LeCun, 2010, Proceedings of 2010 IEEE International Symposium on Circuits and Systems.

Mapping and planning under uncertainty in mobile robots with long-range perception

Yann LeCun, Raia Hadsell, Pierre Sermanet, 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

CNP: An FPGA-based processor for Convolutional Networks

Yann LeCun, Clément Farabet, Jefferson Y. Han, 2009, 2009 International Conference on Field Programmable Logic and Applications.

PROC OF THE IEEE NOVEMBER Gradient Based Learning Applied to Document Recognition

Yoshua Bengio, L. Bottou, Yann LeCun, 2006 .

Globally Trained Handwritten Word Recognizer Using Spatial Representation, Convolutional Neural Networks, and Hidden Markov Models

Yoshua Bengio, Yann LeCun, Donnie Henderson, 1993, NIPS.

Online Learning for Offroad Robots: Spatial Label Propagation to Learn Long-Range Traversability

Yann LeCun, Raia Hadsell, Pierre Sermanet, 2007, Robotics: Science and Systems.

Text Understanding from Scratch pdf

Xiang Zhang, Yann LeCun, Yann LeCun, 2015, ArXiv.

NeuFlow: Dataflow vision processing system-on-a-chip

E. Culurciello, Y. LeCun, B. Martini, 2012, 2012 IEEE 55th International Midwest Symposium on Circuits and Systems (MWSCAS).

Unsupervised Learning of Sparse Features for Scalable Audio Classification

Yann LeCun, Koray Kavukcuoglu, Mikael Henaff, 2011, ISMIR.

Unsupervised Feature Learning from Temporal Data pdf

Jonathan Tompson, Joan Bruna, Yann LeCun, 2015, ICLR.

Structured sparse coding via lateral inhibition

Yann LeCun, Arthur Szlam, Karol Gregor, 2011, NIPS.

Spectral Networks and Locally Connected Networks on Graphs pdf

Joan Bruna, Yann LeCun, Wojciech Zaremba, 2013, ICLR.

Deep Convolutional Networks on Graph-Structured Data pdf

Joan Bruna, Yann LeCun, Mikael Henaff, 2015, ArXiv.

High quality document image compression with "DjVu"

Yoshua Bengio, Yann LeCun, Patrice Y. Simard, 1998, J. Electronic Imaging.

Transformation invariance in pattern recognition: Tangent distance and propagation

Yann LeCun, Patrice Y. Simard, John S. Denker, 2000, Int. J. Imaging Syst. Technol..

Word-level training of a handwritten word recognizer based on convolutional neural networks

Yoshua Bengio, Yann LeCun, Yoshua Bengio, 1994, Proceedings of the 12th IAPR International Conference on Pattern Recognition, Vol. 3 - Conference C: Signal Processing (Cat. No.94CH3440-5).

Fast Approximation of Rotations and Hessians matrices pdf

Yann LeCun, Michaël Mathieu, Michaël Mathieu, 2014, ArXiv.

Off Line Recognition of Handwritten Postal Words Using Neural Networks

Yann LeCun, Jan Ben, Christopher J. C. Burges, 1993, Int. J. Pattern Recognit. Artif. Intell..

Comparing SVM and convolutional networks for epileptic seizure prediction from intracranial EEG

Yann LeCun, P.W. Mirowski, D. Madhavan, 2008, 2008 IEEE Workshop on Machine Learning for Signal Processing.

Browsing through high quality document images with DjVu

Yoshua Bengio, Yann LeCun, Patrice Y. Simard, 1998, Proceedings IEEE International Forum on Research and Technology Advances in Digital Libraries -ADL'98-.

Recurrent Orthogonal Networks and Long-Memory Tasks

Yann LeCun, Arthur Szlam, Mikael Henaff, 2016, ICML.

Fast Incremental Learning for Off-Road Robot Navigation pdf

Lawrence D. Jackel, Yann LeCun, Beat Flepp, 2016, ArXiv.

Learning long-range vision for an offroad robot

Yann LeCun, Raia Hadsell, Yann LeCun, 2008 .

On-Line Learning of Long-Range Obstacle Detection for Off-Road Robots

S. Chopra, Pierre Sermanet, Yury Sulsky, 2006 .

Hybrid hessians for flexible optimization of pose graphs

Yann LeCun, Dragomir Anguelov, Matthew Koichi Grimes, 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Color documents on the Web with DjVu

Pascal Vincent, Yann LeCun, Léon Bottou, 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

Transformation Invariance in Pattern Recognition - Tangent Distance and Tangent Propagation

Yann LeCun, Patrice Y. Simard, John S. Denker, 2012, Neural Networks: Tricks of the Trade.

Effiicient BackProp

Yann LeCun, Klaus-Robert Müller, Genevieve B. Orr, 1996, Neural Networks: Tricks of the Trade.

Discovering the hidden structure of house prices with a non-parametric latent manifold model

Yann LeCun, Andrew Caplin, John Leahy, 2007, KDD '07.

Which Encoding is the Best for Text Classification in Chinese, English, Japanese and Korean? pdf

Xiang Zhang, Yann LeCun, Yann LeCun, 2017, ArXiv.

Efficient off-road localization using visually corrected odometry

Yann LeCun, Matthew Koichi Grimes, Yann LeCun, 2009, 2009 IEEE International Conference on Robotics and Automation.

Universality in halting time and its applications in optimization pdf

Yann LeCun, Levent Sagun, Thomas Trogdon, 2015, ArXiv.

Comparison between Frame-Constrained Fix-Pixel-Value and Frame-Free Spiking-Dynamic-Pixel ConvNets for Visual Processing

Bernabe Linares-Barranco, Eugenio Culurciello, Yann LeCun, 2012, Front. Neurosci..

GEMINI: Gradient Estimation Through Matrix Inversion After Noise Injection

Geoffrey E. Hinton, Yann LeCun, Conrad C. Galland, 1988, NIPS.

Semantic Road Segmentation via Multi-scale Ensembles of Learned Features

Yann LeCun, Theo Gevers, Antonio M. López, 2012, ECCV Workshops.

Reading checks with multilayer graph transformer networks

Yoshua Bengio, Yann LeCun, Léon Bottou, 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

Discriminative feature and model design for automatic speech recognition

Yoshua Bengio, Yann LeCun, Mazin G. Rahim, 1997, EUROSPEECH.

Model-Predictive Policy Learning with Uncertainty Regularization for Driving in Dense Traffic pdf

Yann LeCun, Mikael Henaff, Alfredo Canziani, 2019, ICLR.

DjVu: analyzing and compressing scanned documents for Internet distribution

Yann LeCun, Léon Bottou, Patrick Haffner, 1999, Proceedings of the Fifth International Conference on Document Analysis and Recognition. ICDAR '99 (Cat. No.PR00318).

Universal halting times in optimization and machine learning

Yann LeCun, Levent Sagun, Thomas Trogdon, 2015, 1511.06444.

Deep learning & convolutional networks

Yann LeCun, Yann LeCun, 2015, 2015 IEEE Hot Chips 27 Symposium (HCS).

Singularity of the Hessian in Deep Learning pdf

Yann LeCun, Léon Bottou, Levent Sagun, 2016, ArXiv.

Road Scene Segmentation from a Single Image

Yann LeCun, Theo Gevers, Antonio M. López, 2012, ECCV.

Dynamic Factor Graphs for Time Series Modeling

Yann LeCun, Piotr W. Mirowski, Yann LeCun, 2009, ECML/PKDD.

Real Time Voice Processing with Audiovisual Feedback: Toward Autonomous Agents with Perfect Pitch

Yann LeCun, Daniel D. Lee, Lawrence K. Saul, 2002, NIPS.

Generalization using back-propagation

Yann LeCun, Patrick Gallinari, S. Thiria, 1987 .

Moving Beyond Feature Design: Deep Architectures and Automatic Feature Learning in Music Informatics

Yann LeCun, Juan Pablo Bello, Eric J. Humphrey, 2012, ISMIR.

Source separation with scattering Non-Negative Matrix Factorization

Joan Bruna, Yann LeCun, Pablo Sprechmann, 2015, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

On the applications of multimedia processing to communications

Behzad Shahraray, Yann LeCun, R. V. Cox, 1998, Proc. IEEE.

Flexible-cost slam

Yann LeCun, Matthew Koichi Grimes, Yann LeCun, 2012 .

Feature learning and deep architectures: new directions for music informatics

Yann LeCun, Juan Pablo Bello, Eric J. Humphrey, 2013, Journal of Intelligent Information Systems.

Automatic recognition of biological particles in microscopic images

Pietro Perona, Marc'Aurelio Ranzato, Yann LeCun, 2007, Pattern Recognit. Lett..

Guest Editorial Applications Of Artificial Neural Networks To Image Processing

Aggelos K. Katsaggelos, Rama Chellappa, Sun-Yuan Kung, 1998, IEEE Trans. Image Process..

Learning Stable Group Invariant Representations with Convolutional Networks pdf

Joan Bruna, Yann LeCun, Arthur Szlam, 2013, ICLR.

Differentially- and non-differentially-private random decision trees pdf

Yann LeCun, Mariusz Bojarski, Krzysztof Choromanski, 2014, ArXiv.

Real-Time Continuous Pose Recovery of Human Hands Using Convolutional Networks

Ken Perlin, Jonathan Tompson, Yann LeCun, 2014, ACM Trans. Graph..

Image and video coding-emerging standards and beyond

Jörn Ostermann, Yann LeCun, Lawrence R. Rabiner, 1998, IEEE Trans. Circuits Syst. Video Technol..

Factor Graphs for Relational Regression

Yann LeCun, Sumit Chopra, S. Chopra, 2008 .

High Performance Computer Acoustic Data Accelerator: A New System for Exploring Marine Mammal Acoustics for Big Data Applications pdf

Hervé Glotin, Yann LeCun, Christopher W. Clark, 2015, ArXiv.

Learning Invariant Feature Hierarchies

Yann LeCun, Yann LeCun, 2012, ECCV Workshops.

Graph transformer networks for image recognition

Yann LeCun, Léon Bottou, L. Bottou, 2005 .

Very Deep Convolutional Networks for Text Classification

Yann LeCun, Holger Schwenk, Loïc Barrault, 2016, EACL.

Comparing dynamics: deep neural networks versus glassy systems

Yann LeCun, Levent Sagun, Matthieu Wyart, 2018, ICML.

COMPARISON OF LEARNING ALGORITHMS FOR

L. Bottou, I. Guyon, Yann LeCun, 1995 .

Inspirational Adversarial Image Generation

Yann LeCun, O. Teytaud, C. Couprie, 2019, ArXiv.

+ YY ’ Z X-Residual Prediction Error TargetPredictionObservation Latent 0 State φ f 1 f 2

Yann LeCun, Mikael Henaff, J. Zhao, 2017 .

Learning invariant features through topographic filter maps

R. Fergus, K. Kavukcuoglu, Yann LeCun, 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

Building an Automatic Phenotyping System of Developing Embryos

Yann LeCun, F. Ning, 2006 .

Second Order Properties of Error Surfaces: Learning Time and Generalization

Yann LeCun, S. Solla, I. Kanter, 1990, NIPS 1990.

1 Efficient BackProp

L. Bottou, Yann LeCun, G. Orr, 2012 .

Neural Potts Model

Yann LeCun, Zeming Lin, Brandon Amos, 2021, bioRxiv.

Energy-Based Factor Graphs for Prediction in Relational Data

S. Chopra, Yann LeCun, 2007 .

Word normalization for online handwritten word recognition

Yoshua Bengio, Yann LeCun, Yoshua Bengio, 1994, Proceedings of the 12th IAPR International Conference on Pattern Recognition, Vol. 3 - Conference C: Signal Processing (Cat. No.94CH3440-5).

Automatic Learning Rate Maximization by On-Line Estimation of the Hessian's Eigenvectors

Barak A. Pearlmutter, Yann LeCun, P. Simard, 1992, NIPS 1992.

COMPARISONOFLEARNING ALGORITHMS FORHANDWRITTEN DIGIT RECOGNITION

L. Bottou, I. Guyon, Yann LeCun, 1995 .

OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks

R. Fergus, Pierre Sermanet, Michaël Mathieu, 2013, ICLR.

Learning with Reflective Likelihoods

Yann LeCun, David M. Blei, Kyunghyun Cho, 2018 .

Workshop summary: Workshop on learning feature hierarchies

Geoffrey E. Hinton, Yoshua Bengio, Yann LeCun, 2009, ICML '09.

Sticky Reasoning within Learning Representations

Yann LeCun, Yann LeCun, 2019 .

OPTICAL CHARACTER RECOGNTION FOR AUTOMATIC TELLER MACHINES

Lawrence D. Jackel, Yann LeCun, C. E. Stenard, 1998 .

Second Order Properties of Error Surfaces

Yann LeCun, Ido Kanter, Sara A. Solla, 1990, NIPS.

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, Yann LeCun, C. Clark, 2016, ArXiv.

On-line handwriting recognition with neural networks: Spatial representation versus temporal representation

Yoshua Bengio, Yann LeCun, L. D. Jackel, 1993 .

Image and video coding—emerging standards and beyond

Yann LeCun, M. Reha Civanlar, Joern Ostermann, 2001 .

Neural Information Processing (ICONIP 2013)

Tapani Raiko, Harri Valpola, Yann LeCun, 2013 .

Predictive network modeling of the high-resolution dynamic plant transcriptome in response to nitrate

Yann LeCun, Gabriel Krouk, Piotr Mirowski, 2010, Genome Biology.

Deep learning with elastic averaging SGD: 3rd International Conference on Learning Representations, ICLR 2015

Yann LeCun, Anna Choromanska, Sixin Zhang, 2015, ICLR 2015.

Energy-based Generative Adversarial Networks

Yann LeCun, Junbo Jake Zhao, Michaël Mathieu, 2016, ICLR.

The NIPS workshop on Deep Learning and Unsupervised Feature Learning

Tapani Raiko, Harri Valpola, Yann LeCun, 2011 .

Advances in neural information processing systems: Proceedings of the first 12 conferences (CDROM)

Yann LeCun, Sara A. Solla, Michael I. Jordan, 2001 .

Proceedings : 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition : CVPR 2006 : June 17-22, 2006, New York, NY

Yann LeCun, Andrew Fitzgibbon, C. J. Taylor, 2006 .

Fast training of convolutional networks through FFTS: International Conference on Learning Representations (ICLR2014), CBLS, April 2014

Yann LeCun, Mikael Henaff, Michael Mathieu, 2014, ICLR 2014.

Using curvature information to improve back-propagation

Yann LeCun, Yann LeCun, 1988, Neural Networks.

Memoires associatives distribuees: Une comparaison (Distributed associative memories: A comparison)

Yann LeCun, Patrick Gallinari, S. Thiria, 1987 .

Discriminative recurrent sparse auto-encoders: 1st International Conference on Learning Representations, ICLR 2013

Yann LeCun, Jason Tyler Rolfe, Yann LeCun, 2013, ICLR 2013.

AAAI Workshop - Technical Report: Preface

Benjamin Kuipers, Clayton T. Morrison, Yann LeCun, 2013, AAAI 2013.

Indoor semantic segmentation using depth information: 1st International Conference on Learning Representations, ICLR 2013

Yann LeCun, Camille Couprie, Clément Farabet, 2013, ICLR 2013.

Learning on automata networks

Yann LeCun, Patrick Gallinari, S. Thiria, 1987 .

Computeur Vision and Pattern Recognition (CVPR). Conference

Yann LeCun, Camillo J. Taylor, Andrew Fitzgibbon, 2008, CVPR 2008.

Saturating auto-encoders: International Conference on Learning Representations, ICLR 2013

Yann LeCun, Rostislav Goroshin, Yann LeCun, 2013, ICLR 2013.

Automatic Learning Rate Maximization in Large Adaptive Machines

Barak A. Pearlmutter, Yann LeCun, Patrice Y. Simard, 1992, NIPS.

Learning methods for generic object recognition with invariance to pose and lighting

Yann LeCun, Léon Bottou, Fu Jie Huang, 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

E cient Learning of Sparse Overcomplete Representations with an Energy-Based Model

Marc'Aurelio Ranzato, Yann LeCun, Christopher S. Poultney, 2006, NIPS 2006.

User manual: SN: A simulator for connectionist models

Léon Bottou, Yann LeCun, L. Bottou, 1988 .

Reassessing FHA Risk

Joseph S. Tracy, S. Chopra, Yann LeCun, 2010 .

A Sparse and Locally Shift Invariant Feature Extractor Applied to Document Images

Yann LeCun, Marc'Aurelio Ranzato, 2007, Ninth International Conference on Document Analysis and Recognition (ICDAR 2007).

Marathi Handwritten Numeral Recognition using Fourier Descriptors and Normalized Chain Code

Yoshua Bengio, L. Bottou, Yann LeCun, 2017 .

Contrastive and Non-Contrastive Self-Supervised Learning Recover Global and Local Spectral Embedding Methods

Yann LeCun, Randall Balestriero, 2022, NeurIPS.

Masked Siamese ConvNets

Yann LeCun, L. Jing, Jiachen Zhu, 2022, ArXiv.

TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning

Yann LeCun, A. Canziani, Jiachen Zhu, 2022, ArXiv.

Intra-Instance VICReg: Bag of Self-Supervised Image Patch Embedding

Yann LeCun, Yubei Chen, Adrien Bardes, 2022, ArXiv.

On the duality between contrastive and non-contrastive self-supervised learning

Yann LeCun, Laurent Najman, Yubei Chen, 2022, ArXiv.

A survey on recent activation functions with emphasis on oscillating activation functions

Yoshua Bengio, Yann LeCun, Bhavya Raitani, 2022 .

Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors

Yann LeCun, Sanyam Kapoor, Ravid Shwartz-Ziv, 2022, NeurIPS.

What Do We Maximize in Self-Supervised Learning?

Yann LeCun, Ravid Shwartz-Ziv, Randall Balestriero, 2022, ArXiv.

Coarse-to-Fine Vision-Language Pre-training with Fusion in the Backbone

Yann LeCun, Jianfeng Gao, Zi-Yi Dou, 2022, ArXiv.

Open Research Online Knowledge Graph Construction with a façade: a uniﬁed method to access heterogeneous data sources on the Web

Yann LeCun, Luigi Asprino, 2022 .

Decoupled Contrastive Learning

Yann LeCun, Tyng-Luh Liu, Yubei Chen, 2021, ECCV.

Intra-Instance VICReg: Bag of Self-Supervised Image Patch Embedding

Yann LeCun, Yubei Chen, Adrien Bardes, 2022, ArXiv.

A Path Towards Autonomous Machine Intelligence Version 0.9.2, 2022-06-27

Yann LeCun, Courant, 2022 .

Sparse Coding with Multi-Layer Decoders using Variance Regularization

Yann LeCun, Katrina Evtimova, 2021, Trans. Mach. Learn. Res..

Variance Covariance Regularization Enforces Pairwise Independence in Self-Supervised Representations

Yann LeCun, Randall Balestriero, Grégoire Mialon, 2022, ArXiv.

Minimalistic Unsupervised Learning with the Sparse Manifold Transform

Yann LeCun, B. Olshausen, Y. Ma, 2022, arXiv.org.

VoLTA: Vision-Language Transformer with Weakly-Supervised Local-Feature Alignment

Yann LeCun, Ramalingam Chellappa, Li Jing, 2022, arXiv.org.

Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution

Eero P. Simoncelli, Doris Y. Tsao, Adam H. Marblestone, 2022, ArXiv.

projUNN: efficient method for training deep networks with unitary matrices

Yann LeCun, S. Lloyd, Randall Balestriero, 2022, NeurIPS.

Coarse-to-Fine Vision-Language Pre-training with Fusion in the Backbone

Yann LeCun, Jianfeng Gao, Zi-Yi Dou, 2022, ArXiv.

Compact and Optimal Deep Learning with Recurrent Parameter Generators

Stella X. Yu, Yann LeCun, Brian Cheung, 2021, 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).

Recurrent Parameter Generators

Stella X. Yu, Yann LeCun, Brian Cheung, 2021, arXiv.org.

POLICE: Provably Optimal Linear Constraint Enforcement for Deep Neural Networks

Yann LeCun, Randall Balestriero, 2022, ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Universality in halting time

Yann LeCun, Levent Sagun, T. Trogdon, 2017 .

POLICE: Provably Optimal Linear Constraint Enforcement for Deep Neural Networks

Yann LeCun, Randall Balestriero, 2022, arXiv.org.

Light-weight probing of unsupervised representations for Reinforcement Learning

Yann LeCun, Wancong Zhang, Anthony GX-Chen, 2022, ArXiv.

VICRegL: Self-Supervised Learning of Local Visual Features

Yann LeCun, J. Ponce, Adrien Bardes, 2022, NeurIPS.

Masked Siamese ConvNets

Yann LeCun, L. Jing, Jiachen Zhu, 2022, ArXiv.

Barlow Twins: Self-Supervised Learning via Redundancy Reduction

Yann LeCun, Ishan Misra, Li Jing, 2021, ICML.

Joint Embedding Predictive Architectures Focus on Slow Features

Kyunghyun Cho, Yann LeCun, Vlad Sobal, 2022, ArXiv.

Unsupervised Learning of Structured Representations via Closed-Loop Transcription

Yann LeCun, Y. Ma, Yubei Chen, 2022, ArXiv.

RankMe: Assessing the downstream performance of pretrained self-supervised representations by their rank

Yann LeCun, Laurent Najman, Randall Balestriero, 2022, arXiv.org.

Joint Embedding Self-Supervised Learning in the Kernel Regime

Yann LeCun, Randall Balestriero, Yubei Chen, 2022, ArXiv.

TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning

Yann LeCun, A. Canziani, Jiachen Zhu, 2022, ArXiv.

On the duality between contrastive and non-contrastive self-supervised learning

Yann LeCun, Laurent Najman, Yubei Chen, 2022, ArXiv.

VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning

Yann LeCun, J. Ponce, Adrien Bardes, 2021, ICLR.

Coarse-to-Fine Vision-Language Pre-training with Fusion in the Backbone

Yann LeCun, Jianfeng Gao, Zi-Yi Dou, 2022, NeurIPS.

Final thesis for the fulfilment of the requirements for the degree of MSc. in Applied Computing Science Improving Score Matching for learning statistical models of natural images

Y. LeCun, Yann LeCun, 2010 .

What is the Best Feature Learning Procedure in Hierarchical Recognition Architectures? pdf

Yann LeCun, Koray Kavukcuoglu, Karol Gregor, 2016, ArXiv.

Unsupervised Learning of Spatiotemporally Coherent Metrics

Jonathan Tompson, Joan Bruna, Yann LeCun, 2014, 2015 IEEE International Conference on Computer Vision (ICCV).

Discriminative Recurrent Sparse Auto-Encoders pdf

Yann LeCun, Jason Tyler Rolfe, Yann LeCun, 2013, ICLR.

Saturating Auto-Encoders

Yann LeCun, Rostislav Goroshin, Yann LeCun, 2013, ICLR 2013.

Ask the locals: Multi-way local pooling for image recognition

Nicolas Le Roux, Jean Ponce, Y-Lan Boureau, 2011, 2011 International Conference on Computer Vision.

Large-Scale FPGA-based Convolutional Networks

Berin Martini, Eugenio Culurciello, Yann LeCun, 2011 .

Convolutional Matching Pursuit and Dictionary Training pdf

Yann LeCun, Koray Kavukcuoglu, Arthur Szlam, 2010, ArXiv.

Learning Feature Hierarchies for Object Recognition

Yann LeCun, Koray Kavukcuoglu, K. Kavukcuoglu, 2010 .

What is the best multi-stage architecture for object recognition?

Yann LeCun, Koray Kavukcuoglu, Kevin Jarrett, 2009, 2009 IEEE 12th International Conference on Computer Vision.

Deep Learning

Geoffrey E. Hinton, Yoshua Bengio, Aaron C. Courville, 2015, Nature.

Pushing Stochastic Gradient towards Second-Order Methods -- Backpropagation Learning with Transformations in Nonlinearities

Tapani Raiko, Harri Valpola, Yann LeCun, 2013, ICLR.

Deep learning, reinforcement learning, and world models

Yann LeCun, Doina Precup, M. Sahani, 2022, Neural Networks.

MDETR - Modulated Detection for End-to-End Multi-Modal Understanding pdf

Yann LeCun, Nicolas Carion, Gabriel Synnaeve, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

Predicting Deeper into the Future of Semantic Segmentation

Yann LeCun, Camille Couprie, Pauline Luc, 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

Deep learning for AI

Geoffrey E. Hinton, Yoshua Bengio, Yann Lecun, 2021, Commun. ACM.

Guest Editorial: Deep Learning

Geoffrey E. Hinton, Yann LeCun, M. Ranzato, 2015, International Journal of Computer Vision.

Efficient Learning of Sparse Invariant Representations pdf

Yann LeCun, Karol Gregor, Yann LeCun, 2011, ArXiv.

Unsupervised Learning of Feature Hierarchies

Marc'Aurelio Ranzato, Yann LeCun, Yann LeCun, 2009 .

OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks pdf

Xiang Zhang, Yann LeCun, Pierre Sermanet, 2013, ICLR.

DCL System Using Deep Learning Approaches for Land-Based or Ship-Based Real-Time Recognition and Localization of Marine Mammals

Christopher W. Clark, Peter J. Dugan, Sofie M. Van Parijs, 2013 .

DCL System Research Using Advanced Approaches for Land-based or Ship-based Real-Time Recognition and Localization of Marine Mammals

Christopher W. Clark, Peter J. Dugan, Sofie M. Van Parijs, 2012 .

Augmented Language Models: a Survey

Yann LeCun, Edouard Grave, Ramakanth Pasunuru, 2023, ArXiv.

Indoor Semantic Segmentation using depth information pdf

Yann LeCun, Camille Couprie, Clément Farabet, 2013, ICLR.

A Tutorial on Energy-Based Learning

Fu Jie Huang, Y. LeCun, S. Chopra, 2006 .

Learning maneuver dictionaries for ground robot planning

Urs A. Muller, Yann LeCun, Pierre Sermanet, 2008 .

Hardware accelerated visual attention algorithm

Berin Martini, Eugenio Culurciello, Yann LeCun, 2011, 2011 45th Annual Conference on Information Sciences and Systems.

Design Inspiration from Generative Networks

Yann LeCun, Camille Couprie, Antoine Bordes, 2018 .

The SSL Interplay: Augmentations, Inductive Bias, and Generalization

Vivien A. Cabannes, Yann LeCun, Randall Balestriero, 2023, ArXiv.

Understanding Dimensional Collapse in Contrastive Self-supervised Learning pdf

Yann LeCun, Yuandong Tian, Li Jing, 2021, ICLR.

The Mind of a Mouse

Bruce R. Rosen, Terrence J. Sejnowski, Yann LeCun, 2020, Cell.

How can neural networks learn the rich internal representations required for difficult tasks such as recognizing objects or understanding language ?

Geoffrey E. Hinton, Yoshua Bengio, Yann LeCun, 2021 .

Stereo Matching by Training a Convolutional Neural Network to Compare Image Patches

Yann LeCun, Jure Zbontar, Yann LeCun, 2015, J. Mach. Learn. Res..

Concerto for violin and Markov model

Yann LeCun, Juan Pablo Bello, Robert Rowe, 2011, Commun. ACM.

The Effects of Regularization and Data Augmentation are Class Dependent

L. Bottou, Yann LeCun, Randall Balestriero, 2022, NeurIPS.

Adversarially Regularized Autoencoders

Alexander M. Rush, Yann LeCun, Yoon Kim, 2017, ICML.

Universum Prescription: Regularization Using Unlabeled Data

Xiang Zhang, Yann LeCun, Yann LeCun, 2015, AAAI.

Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution

Eero P. Simoncelli, Doris Y. Tsao, Adam H. Marblestone, 2022, ArXiv.

Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture

Michael G. Rabbat, Yann LeCun, Nicolas Ballas, 2023, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

A Cookbook of Self-Supervised Learning

Ari S. Morcos, Yann LeCun, H. Pirsiavash, 2023, ArXiv.

Self-supervised learning of Split Invariant Equivariant representations

Yann LeCun, Laurent Najman, Q. Garrido, 2023, ArXiv.

A Data-Augmentation Is Worth A Thousand Samples: Exact Quantification From Analytical Augmented Sample Moments

Yann LeCun, Ishan Misra, Randall Balestriero, 2022, arXiv.org.

Computing the stereo matching cost with a convolutional neural network

Yann LeCun, Jure Zbontar, Yann LeCun, 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

EMP-SSL: Towards Self-Supervised Learning in One Training Epoch

Yann LeCun, Y. Ma, Yubei Chen, 2023, ArXiv.

Neural Manifold Clustering and Embedding

Yann LeCun, Friedrich T. Sommer, Zengyi Li, 2022, ArXiv.

Transformer visualization via dictionary learning: contextualized embedding as a linear superposition of transformer factors

Yann LeCun, B. Olshausen, Yubei Chen, 2021, DEELIO.

Learning to Linearize Under Uncertainty

Yann LeCun, Michaël Mathieu, Ross Goroshin, 2015, NIPS.

Minimalistic Unsupervised Learning with the Sparse Manifold Transform

Yann LeCun, B. Olshausen, Y. Ma, 2022, ArXiv.

VoLTA: Vision-Language Transformer with Weakly-Supervised Local-Feature Alignment

Yann LeCun, Ramalingam Chellappa, Li Jing, 2022, ArXiv.

Memory-based character recognition using a transformation invariant metric

Yann LeCun, Patrice Y. Simard, John S. Denker, 1994, Proceedings of the 12th IAPR International Conference on Pattern Recognition, Vol. 3 - Conference C: Signal Processing (Cat. No.94CH3440-5).

RankMe: Assessing the downstream performance of pretrained self-supervised representations by their rank

Yann LeCun, Laurent Najman, Randall Balestriero, 2022, ArXiv.

Active Self-Supervised Learning: A Few Low-Cost Relationships Are All You Need

Vivien A. Cabannes, L. Bottou, Yann LeCun, 2023, ArXiv.

Time-Delay Neural Networks and Independent Component Analysis for EEG-Based Prediction of Epileptic Seizures Propagation

Yann LeCun, Deepak Madhavan, Piotr W. Mirowski, 2007, AAAI.

Very deep multilingual convolutional neural networks for LVCSR

Brian Kingsbury, Yann LeCun, Tom Sercu, 2015, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Global training of document processing systems using graph transformer networks

Yoshua Bengio, Yann LeCun, Léon Bottou, 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

Regularized estimation of image statistics by Score Matching

Yann LeCun, Diederik P. Kingma, Yann LeCun, 2010, NIPS.

Machine Learning and the Spatial Structure of House Prices and Housing Returns

Yann LeCun, Andrew Caplin, Sumit Chopra, 2008 .

Disentangling factors of variation in deep representation using adversarial training

Yann LeCun, Junbo Jake Zhao, Aditya Ramesh, 2016, NIPS.

Adversarially Regularized Autoencoders for Generating Discrete Structures pdf

Alexander M. Rush, Yann LeCun, Yoon Kim, 2017, ArXiv.

Predicting Future Instance Segmentations by Forecasting Convolutional Features pdf

Yann LeCun, Camille Couprie, Pauline Luc, 2018, ECCV.

A hierarchical loss and its problems when classifying non-hierarchically

Mark Tygert, Yann LeCun, Cinna Wu, 2017, PloS one.

Separating the World and Ego Models for Self-Driving

Kyunghyun Cho, Yann LeCun, A. Canziani, 2022, ArXiv.

Toward real-time indoor semantic segmentation using depth information

Yann LeCun, Camille Couprie, Clément Farabet, 2014 .

Prediction Under Uncertainty with Error-Encoding Networks pdf

Yann LeCun, Mikael Henaff, Junbo Jake Zhao, 2017, ArXiv.

A Generalization of ViT/MLP-Mixer to Graphs

Yann LeCun, T. Laurent, X. Bresson, 2022, ArXiv.

S EPARATING THE W ORLD AND E GO M ODELS FOR S ELF -D RIVING

Kyunghyun Cho, Yann LeCun, A. Canziani, 2022 .

Catalyzing next-generation Artificial Intelligence through NeuroAI

Eero P. Simoncelli, Konrad Paul Kording, Blake A. Richards, 2023, Nature Communications.

A Mathematical Motivation for Complex-Valued Convolutional Networks

Mark Tygert, Joan Bruna, Yann LeCun, 2015, Neural Computation.

Learning in High Dimension Always Amounts to Extrapolation pdf

Yann LeCun, Randall Balestriero, Jerome Pesenti, 2021, ArXiv.

Eigenvalues of the Hessian in Deep Learning: Singularity and Beyond

Yann LeCun, Levent Sagun, Leon Bottou, 2016, 1611.07476.

Binary embeddings with structured hashed projections

Sanjiv Kumar, Yann LeCun, Mariusz Bojarski, 2015, ICML.

Reverse Engineering Self-Supervised Learning

Yann LeCun, Ravid Shwartz-Ziv, S. Dekel, 2023, ArXiv.

RankMe: Assessing the downstream performance of pretrained self-supervised representations by their rank

Yann LeCun, Laurent Najman, Randall Balestriero, 2022, ICML.

A Generalization of ViT/MLP-Mixer to Graphs

Yann LeCun, T. Laurent, X. Bresson, 2022, ICML.

Tracking the World State with Recurrent Entity Networks pdf

Jason Weston, Yann LeCun, Antoine Bordes, 2016, ICLR.

M INIMALISTIC U NSUPERVISED R EPRESENTATION L EARNING WITH THE S PARSE M ANIFOLD T RANS - FORM

Yann LeCun, B. Olshausen, Yubei Chen, 2023 .

A Cookbook of Self-Supervised Learning

Ari S. Morcos, Yann LeCun, H. Pirsiavash, 2023, ArXiv.

Self-Supervised Learning with Lie Symmetries for Partial Differential Equations

Yann LeCun, Danyal Rehman, B. Kiani, 2023, NeurIPS.

Implicit Rank-Minimizing Autoencoder pdf

Yann LeCun, Li Jing, Jure Zbontar, 2020, NeurIPS.

Complex-valued convolutional networks yield data-driven multiscale windowed spectra

Mark Tygert, Joan Bruna, Yann LeCun, 2015 .

Learning about an exponential amount of conditional distributions

Yann LeCun, David Lopez-Paz, Maxime Oquab, 2019, NeurIPS.

Variance-Covariance Regularization Improves Representation Learning

Yann LeCun, Ravid Shwartz-Ziv, Yubei Chen, 2023, ArXiv.

To Compress or Not to Compress - Self-Supervised Learning and Information Theory: A Review

Yann LeCun, Ravid Shwartz-Ziv, 2023, ArXiv.

An Information-Theoretic Perspective on Variance-Invariance-Covariance Regularization

Tim G. J. Rudner, Yann LeCun, Kenji Kawaguchi, 2023, ArXiv.

Audio Source Separation with Discriminative Scattering Networks

Joan Bruna, Yann LeCun, Pablo Sprechmann, 2014, LVA/ICA.

Spectral Networks and Deep Locally Connected Networks on Graphs

Yann LeCun, Wojciech Zaremba, Joan Bruna, 2014 .

MC-JEPA: A Joint-Embedding Predictive Architecture for Self-Supervised Learning of Motion and Content Features

Yann LeCun, J. Ponce, Adrien Bardes, 2023, ArXiv.

The SSL Interplay: Augmentations, Inductive Bias, and Generalization

Vivien A. Cabannes, Yann LeCun, Randall Balestriero, 2023, ICML.

Adversarially-Trained Normalized Noisy-Feature Auto-Encoder for Text Generation pdf

Yann LeCun, Xiang Zhang, Yann LeCun, 2018, ArXiv.

Minimalistic Unsupervised Representation Learning with the Sparse Manifold Transform

Yann LeCun, B. Olshausen, Yubei Chen, 2023, ICLR.

Extracting structural folding pattern of chromatin using chromatin condensation data using HiCNN[12] or HiCNN2[13] approaches Metrics for evaluation: Comparing the result’s mean squared error and Pearson’s correlation coefficients with experimental high-resolution Hi-C data

R. Socher, Yann LeCun, J. Denker, 2022 .

Fast Approximations to Structured Sparse Coding and Applications to Object Classification pdf

Yann LeCun, Arthur Szlam, Karol Gregor, 2012, ECCV.

Geometric Deep Learning: Going beyond Euclidean data

Yann LeCun, Joan Bruna, M. Bronstein, 2017, IEEE Signal Processing Magazine.

Self-supervised learning of Split Invariant Equivariant representations

Yann LeCun, Laurent Najman, Q. Garrido, 2023, ICML.

On the duality between contrastive and non-contrastive self-supervised learning

Yann LeCun, Laurent Najman, Yubei Chen, 2022, ICLR.

Pattern Recognition

Yoshua Bengio, Yann LeCun, Yoshua Bengio, 1998, Lecture Notes in Computer Science.

Blockwise Self-Supervised Learning at Scale

Shoaib Ahmed Siddiqui, Yann LeCun, David Krueger, 2023, ArXiv.

A Spectral Regularizer for Unsupervised Disentanglement pdf

Yann LeCun, Aditya Ramesh, Youngduck Choi, 2018, ArXiv.

Learning by teaching.

Bertram C. Bruce, Susanne P. Lajoie, Segismundo S. Izquierdo, 1977, The Australian nurses' journal. Royal Australian Nursing Federation.

Causal graph-based video segmentation

Yann LeCun, Camille Couprie, Clément Farabet, 2013, 2013 IEEE International Conference on Image Processing.

Statistical Machine Learning and Dissolved Gas Analysis: A Review

P. Mirowski, Y. LeCun, Yann LeCun, 2012, IEEE Transactions on Power Delivery.

Bag of Image Patch Embedding Behind the Success of Self-Supervised Learning

Yann LeCun, Yubei Chen, Adrien Bardes, 2022, 2206.08954.

Classification of patterns of EEG synchronization for seizure prediction

Yann LeCun, D. Madhavan, R. Kuzniecky, 2009, Clinical Neurophysiology.

Police: Provably Optimal Linear Constraint Enforcement For Deep Neural Networks

Yann LeCun, Randall Balestriero, 2022, IEEE International Conference on Acoustics, Speech, and Signal Processing.

The role of over-parametrization in generalization of neural networks

Yann LeCun, Srinadh Bhojanapalli, Behnam Neyshabur, 2019, ICLR.

Predicting masked tokens in stochastic locations improves masked image modeling

Yann LeCun, Trevor Darrell, Nicolas Ballas, 2023, ArXiv.

GLoMo: Unsupervisedly Learned Relational Graphs as Transferable Representations pdf

Yann LeCun, Ruslan Salakhutdinov, William W. Cohen, 2018, ArXiv.

To Compress or Not to Compress - Self-Supervised Learning and Information Theory: A Review

Yann LeCun, Ravid Shwartz-Ziv, 2023, ArXiv.

Active Self-Supervised Learning: A Few Low-Cost Relationships Are All You Need

Vivien A. Cabannes, L. Bottou, Yann LeCun, 2023, ArXiv.

A Mathematical Motivation for Complex-Valued Convolutional Networks

Yann LeCun, Joan Bruna, M. Tygert, 2015, Neural Computation.

Learning by teaching.

Bertram C. Bruce, Susanne P. Lajoie, Segismundo S. Izquierdo, 1977, The Australian nurses' journal. Royal Australian Nursing Federation.

Language, common sense, and the Winograd schema challenge

Yann LeCun, Jacob Browning, 2023, Artif. Intell..

Deep Learning

Geoffrey E. Hinton, Yoshua Bengio, Yann LeCun, 2015 .

Pattern Recognition and Neural Networks

Yoshua, Yoshua Bengio, Yann LeCun, 1995 .

Jean piaget theory in punjabi pdf

Yann LeCun, J. Piaget, J. Bruner, 2020 .