Yann LeCun

245.9k citations

192 papers · 133.0k indexed · 32 hit papers · h-index 67

Impact in

Computer Vision and Pattern Recognition top 0.01%
- Advanced Neural Network Applications
- Advanced Image and Video Retrieval Techniques
- Video Surveillance and Tracking Methods
- Human Pose and Action Recognition
Artificial Intelligence top 0.01%
- Anomaly Detection Techniques and Applications
- Domain Adaptation and Few-Shot Learning
- Neural Networks and Applications

Papers in

Computer Vision and Pattern Recognition 111
- Advanced Image and Video Retrieval Techniques 28
- Handwritten Text Recognition Techniques 22
- Advanced Neural Network Applications 19
- Generative Adversarial Networks and Image Synthesis 16
- Image Retrieval and Classification Techniques 14
Artificial Intelligence 91
- Neural Networks and Applications 36
- Domain Adaptation and Few-Shot Learning 20

Co-authors: Yoshua Bengio Geoffrey E. Hinton Léon Bottou Patrick Haffner Raia Hadsell Sumit Chopra D. Henderson Bernhard E. Boser
Journals: Neural Computation (4 papers)IEEE Transactions on Image Processing (2 papers)Journal of Field Robotics (2 papers)Proceedings of the IEEE (2 papers)Clinical Neurophysiology (1 paper)
Partner nations: United States France Switzerland

In The Last Decade

Yann LeCun

187 papers receiving 127.4k citations

Hit Papers

15 papers align trajectories log scale

Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture 2023 · 117 citations

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if any of the following hold:

it has ≥500 total citations;
it reaches ≥1.5× the top-1% citation threshold for papers in the same subfield and year (the threshold is the minimum needed to enter the top 1%, not the average within it);
it reaches the top citation threshold in at least one of its specific research topics.

2023 Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture
2022 Neural Networks
2021 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
2021 Communications of the ACM
2018 A Closer Look at Spatiotemporal Convolutions for Action Recognition
2017 IEEE Signal Processing Magazine
2015 Efficient object localization using Convolutional Networks
2015 Nature
2014 arXiv (Cornell University)
2014 ACM Transactions on Graphics
2013 Pedestrian Detection with Unsupervised Multi-stage Feature Learning
2012 IEEE Transactions on Pattern Analysis and Machine Intelligence
2011 Traffic sign recognition with multi-scale Convolutional Networks
2010 Learning mid-level features for recognition
2010 SPIRE - Sciences Po Institutional REpository
2010 A Theoretical Analysis of Feature Pooling in Visual Recognition
2010 International Conference on Machine Learning
2009 SPIRE - Sciences Po Institutional REpository
2007 Unsupervised Learning of Invariant Feature Hierarchies with Applications to Object Recognition
2007 Scaling learning algorithms towards AI
2006 A Tutorial on Energy-Based Learning
2006 SPIRE - Sciences Po Institutional REpository
2005 SPIRE - Sciences Po Institutional REpository
2004 Learning methods for generic object recognition with invariance to pose and lighting
2002 Comparison of classifier methods: a case study in handwritten digit recognition
1998 Proceedings of the IEEE
1998 Neural Information Processing Systems
1993 International Journal of Pattern Recognition and Artificial Intelligence
1989 Generalization and network design strategies
1989 Neural Computation
1989 Neural Information Processing Systems
1989 neural information processing systems

Peers

Countries citing papers authored by Yann LeCun

Since Specialization

Citations

This map shows the geographic impact of Yann LeCun's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Yann LeCun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yann LeCun more than expected).

Fields of papers citing papers by Yann LeCun

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yann LeCun. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Yann LeCun. The network helps show where Yann LeCun may publish in the future.

Co-authors

The 25 scholars most cited alongside Yann LeCun, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Yann LeCun Line = papers co-authored together Yann LeCun links everyone, so they are left out of the graph.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work
1	Forgotten Polygons: Multimodal Large Language Models are Shape-Blind William J. Rudman, Michal Golovanevsky, Amir Bar, Vedant Palit, Yann LeCun, Carsten Eickhoff, Ritambhara Singh	2025	1
2	To Compress or Not to Compress—Self-Supervised Learning and Information Theory: A Review Entropy ·Ravid Shwartz Ziv, Yann LeCun	2024	26
3	Gradient-based learning applied to document recognition Yann LeCun	2024	2
4	Transformer visualization via dictionary learning: contextualized embedding as a linear superposition of transformer factors Zeyu Yun, Yubei Chen, Bruno A. Olshausen, Yann LeCun	2021	8
5	Energy-based Generative Adversarial Networks International Conference on Learning Representations ·Junbo Zhao, Michaël Mathieu, Yann LeCun	2017	55
6	Overfeat: Integrated recognition, localization and detection using convolutional networks. 2nd International Conference on Learning Representations, ICLR 2014 International Conference on Learning Representations ·Pierre Sermanet, David Eigen, Xiang Zhang, Michaël Mathieu, Rob Fergus, Yann LeCun	2014	16
7	EXPLORATIONS ON HIGH DIMENSIONAL LANDSCAPES arXiv (Cornell University) ·Levent Sagun, V. Uğur Güney, Gérard Ben Arous, Yann LeCun	2014	1
8	Fast training of convolutional networks through FFTS: International Conference on Learning Representations (ICLR2014), CBLS, April 2014 International Conference on Learning Representations ·Michaël Mathieu, Mikael Henaff, Yann LeCun	2014	5
9	Deep Learning Made Easier by Linear Transformations in Perceptrons International Conference on Artificial Intelligence and Statistics ·Tapani Raiko, Harri Valpola, Yann LeCun	2012	87
10	Semi-supervised learning via generalized maximum entropy International Conference on Artificial Intelligence and Statistics ·Yann LeCun, Alper Nabi Erkan	2010	13
11	Learning maneuver dictionaries for ground robot planning International Symposium on Robotics ·Pierre Sermanet, Marco Scoffier, Chris Crudele, Urs Müller, Yann LeCun	2008	4
12	Unsupervised Learning of Invariant Feature Hierarchies with Applications to Object Recognition Marc’Aurelio Ranzato, Fu Jie Huang, Y-Lan Boureau, Yann LeCun Hit paper breakdown →	2007	699
13	A Unified Energy-Based Framework for Unsupervised Learning International Conference on Artificial Intelligence and Statistics ·Marc’Aurelio Ranzato, Y-Lan Boureau, Sumit Chopra, Yann LeCun	2007	53
14	Efficient BackProp Neural Information Processing Systems ·Yann LeCun, Léon Bottou, Genevieve Orr, Klaus‐Robert Müller Hit paper breakdown →	1998	951
15	Gradient-based learning applied to document recognition Proceedings of the IEEE ·Yann LeCun, Léon Bottou, Yoshua Bengio, Patrick Haffner Hit paper breakdown →	1998	34531
16	Boxlets: A Fast Convolution Algorithm for Signal Processing and Neural Networks neural information processing systems ·Patrice Simard, Léon Bottou, Patrick Haffner, Yann LeCun	1998	81
17	Automatic Learning Rate Maximization by On-Line Estimation of the Hessian's Eigenvectors Maynooth University ePrints and eTheses Archive (Maynooth University) ·Yann LeCun, Patrice Y. Simard, Barak A. Pearlmutter	1993	50
18	Automatic Learning Rate Maximization in Large Adaptive Machines Neural Information Processing Systems ·Yann LeCun, Patrice Simard, Barak A. Pearlmutter	1992	8
19	Transforming Neural-Net Output Levels to Probability Distributions Neural Information Processing Systems ·John S. Denker, Yann LeCun	1990	123
20	Improving the convergence of back-propagation learning with second-order methods Stephen Becker, Yann LeCun	1989	199

About Yann LeCun

Yann LeCun is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing, Human-Computer Interaction and Media Technology, having authored 192 papers that have together received 133.0k indexed citations. Recurring topics across this work include Neural Networks and Applications (36 papers), Advanced Image and Video Retrieval Techniques (28 papers), Handwritten Text Recognition Techniques (22 papers), Domain Adaptation and Few-Shot Learning (20 papers), Advanced Neural Network Applications (19 papers), Generative Adversarial Networks and Image Synthesis (16 papers), Robotics and Sensor-Based Localization (15 papers) and Image Retrieval and Classification Techniques (14 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (47.9k citations), Artificial Intelligence (48.5k citations), Media Technology (8.7k citations), Health Informatics (1.3k citations) and Signal Processing (9.0k citations). Yann LeCun has collaborated with scholars based in United States, France and Switzerland. Frequent co-authors include Yoshua Bengio, Geoffrey E. Hinton, Léon Bottou, Patrick Haffner, Raia Hadsell, Sumit Chopra, D. Henderson, Bernhard E. Boser, Richard Howard and L. D. Jackel. Their work appears in journals such as Neural Computation, IEEE Transactions on Image Processing, Journal of Field Robotics, Proceedings of the IEEE and Clinical Neurophysiology.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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