default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDYann LeCun
Yann André LeCun
Person information
- affiliation: New York University, Courant Institute of Mathematical Sciences, USA
- affiliation: Facebook
- award (2018): Turing Award
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[j48]Wancong Zhang, Anthony GX-Chen, Vlad Sobal, Yann LeCun, Nicolas Carion:
Light-weight Probing of Unsupervised Representations for Reinforcement Learning. RLJ 4: 1924-1949 (2024)- [j47]Ravid Shwartz-Ziv, Yann LeCun:
To Compress or Not to Compress - Self-Supervised Learning and Information Theory: A Review. Entropy 26(3): 252 (2024) - [j46]Li Liu
, Timothy M. Hospedales, Yann LeCun, Mingsheng Long, Jiebo Luo, Wanli Ouyang, Matti Pietikäinen, Tinne Tuytelaars:
Editorial: Learning With Fewer Labels in Computer Vision. IEEE Trans. Pattern Anal. Mach. Intell. 46(3): 1319-1326 (2024) - [j45]Shoaib Ahmed Siddiqui, David Krueger, Yann LeCun, Stéphane Deny:
Blockwise Self-Supervised Learning at Scale. Trans. Mach. Learn. Res. 2024 (2024) - [c182]Shengbang Tong, Zhuang Liu, Yuexiang Zhai, Yi Ma, Yann LeCun, Saining Xie:
Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs. CVPR 2024: 9568-9578 - [c181]Xiaoxin He, Xavier Bresson, Thomas Laurent, Adam Perold, Yann LeCun, Bryan Hooi:
Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning. ICLR 2024 - [c180]Grégoire Mialon, Clémentine Fourrier, Thomas Wolf, Yann LeCun, Thomas Scialom:
GAIA: a benchmark for General AI Assistants. ICLR 2024 - [c179]Randall Balestriero, Yann LeCun:
How Learning by Reconstruction Produces Uninformative Features For Perception. ICML 2024 - [c178]Amir Bar, Florian Bordes, Assaf Shocher, Mido Assran, Pascal Vincent, Nicolas Ballas, Trevor Darrell, Amir Globerson, Yann LeCun:
Stochastic positional embeddings improve masked image modeling. ICML 2024 - [c177]Ori Press, Ravid Shwartz-Ziv, Yann LeCun, Matthias Bethge:
The Entropy Enigma: Success and Failure of Entropy Minimization. ICML 2024 - [i140]Shengbang Tong, Zhuang Liu, Yuexiang Zhai, Yi Ma, Yann LeCun, Saining Xie:
Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs. CoRR abs/2401.06209 (2024) - [i139]Randall Balestriero, Yann LeCun:
Fast and Exact Enumeration of Deep Networks Partitions Regions. CoRR abs/2401.11188 (2024) - [i138]Xiaoxin He, Yijun Tian, Yifei Sun, Nitesh V. Chawla, Thomas Laurent, Yann LeCun, Xavier Bresson, Bryan Hooi:
G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering. CoRR abs/2402.07630 (2024) - [i137]Randall Balestriero, Yann LeCun:
Learning by Reconstruction Produces Uninformative Features For Perception. CoRR abs/2402.11337 (2024) - [i136]Quentin Garrido, Mahmoud Assran, Nicolas Ballas, Adrien Bardes, Laurent Najman, Yann LeCun:
Learning and Leveraging World Models in Visual Representation Learning. CoRR abs/2403.00504 (2024) - [i135]Adrien Bardes, Quentin Garrido, Jean Ponce, Xinlei Chen, Michael G. Rabbat, Yann LeCun, Mahmoud Assran, Nicolas Ballas:
Revisiting Feature Prediction for Learning Visual Representations from Video. CoRR abs/2404.08471 (2024) - [i134]Amir Bar, Arya Bakhtiar, Danny Tran, Antonio Loquercio, Jathushan Rajasegaran, Yann LeCun, Amir Globerson, Trevor Darrell:
EgoPet: Egomotion and Interaction Data from an Animal's Perspective. CoRR abs/2404.09991 (2024) - [i133]Théo Moutakanni, Piotr Bojanowski, Guillaume Chassagnon, Céline Hudelot, Armand Joulin, Yann LeCun, Matthew J. Muckley, Maxime Oquab, Marie-Pierre Revel, Maria Vakalopoulou:
Advancing human-centric AI for robust X-ray analysis through holistic self-supervised learning. CoRR abs/2405.01469 (2024) - [i132]Ori Press, Ravid Shwartz-Ziv, Yann LeCun, Matthias Bethge:
The Entropy Enigma: Success and Failure of Entropy Minimization. CoRR abs/2405.05012 (2024) - [i131]Yuexiang Zhai, Hao Bai, Zipeng Lin, Jiayi Pan, Shengbang Tong, Yifei Zhou, Alane Suhr, Saining Xie, Yann LeCun, Yi Ma, Sergey Levine:
Fine-Tuning Large Vision-Language Models as Decision-Making Agents via Reinforcement Learning. CoRR abs/2405.10292 (2024) - [i130]Adrien Basdevant, Camille François, Victor Storchan, Kevin Bankston, Ayah Bdeir, Brian Behlendorf, Mérouane Debbah, Sayash Kapoor, Yann LeCun, Mark Surman, Helen King-Turvey, Nathan Lambert, Stefano Maffulli, Nik Marda, Govind Shivkumar, Justine Tunney:
Towards a Framework for Openness in Foundation Models: Proceedings from the Columbia Convening on Openness in Artificial Intelligence. CoRR abs/2405.15802 (2024) - [i129]Nicklas Hansen, Jyothir S. V, Vlad Sobal, Yann LeCun, Xiaolong Wang, Hao Su:
Hierarchical World Models as Visual Whole-Body Humanoid Controllers. CoRR abs/2405.18418 (2024) - [i128]Rylan Schaeffer, Victor Lecomte, Dhruv Bhandarkar Pai, Andres Carranza, Berivan Isik, Alyssa Unell, Mikail Khona, Thomas E. Yerxa, Yann LeCun, SueYeon Chung, Andrey Gromov, Ravid Shwartz-Ziv, Sanmi Koyejo:
Towards an Improved Understanding and Utilization of Maximum Manifold Capacity Representations. CoRR abs/2406.09366 (2024) - [i127]Ravid Shwartz-Ziv, Micah Goldblum, Arpit Bansal, C. Bayan Bruss, Yann LeCun, Andrew Gordon Wilson:
Just How Flexible are Neural Networks in Practice? CoRR abs/2406.11463 (2024) - [i126]Shengbang Tong, Ellis Brown, Penghao Wu, Sanghyun Woo, Manoj Middepogu, Sai Charitha Akula, Jihan Yang, Shusheng Yang, Adithya Iyer, Xichen Pan, Austin Wang, Rob Fergus, Yann LeCun, Saining Xie:
Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs. CoRR abs/2406.16860 (2024) - [i125]Colin White, Samuel Dooley, Manley Roberts, Arka Pal, Benjamin Feuer, Siddhartha Jain, Ravid Shwartz-Ziv, Neel Jain, Khalid Saifullah, Siddartha Naidu, Chinmay Hegde, Yann LeCun, Tom Goldstein, Willie Neiswanger, Micah Goldblum:
LiveBench: A Challenging, Contamination-Free LLM Benchmark. CoRR abs/2406.19314 (2024) - [i124]Vlad Sobal, Mark Ibrahim, Randall Balestriero, Vivien Cabannes, Diane Bouchacourt, Pietro Astolfi, Kyunghyun Cho, Yann LeCun:
𝕏-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs. CoRR abs/2407.18134 (2024) - [i123]Alex N. Wang, Christopher Hoang, Yuwen Xiong, Yann LeCun, Mengye Ren:
PooDLe: Pooled and dense self-supervised learning from naturalistic videos. CoRR abs/2408.11208 (2024) - [i122]Jan Witowski, Ken Zeng, Joseph Cappadona, Jailan Elayoubi, Elena Diana Chiru, Nancy Chan, Young-Joon Kang, Frederick Howard, Irina Ostrovnaya, Carlos Fernandez-Granda, Freya Schnabel, Ugur Ozerdem, Kangning Liu, Zoe Steinsnyder, Nitya Thakore, Mohammad Sadic, Frank Yeung, Elisa Liu, Theodore Hill, Benjamin Swett, Danielle Rigau, Andrew Clayburn, Valerie Speirs, Marcus Vetter, Lina Sojak, Simone Muenst Soysal, Daniel Baumhoer, Khalil Choucair, Yu Zong, Lina Daoud, Anas Saad, Waleed Abdulsattar, Rafic Beydoun, Jia-Wern Pan, Haslina Makmur, Soo-Hwang Teo, Linda Ma Pak, Victor Angel, Dovile Zilenaite-Petrulaitiene, Arvydas Laurinavicius, Natalie Klar, Brian D. Piening, Carlo Bifulco, Sun-Young Jun, Jae Pak Yi, Su Hyun Lim, Adam Brufsky, Francisco J. Esteva, Lajos Pusztai, Yann LeCun, Krzysztof J. Geras:
Multi-modal AI for comprehensive breast cancer prognostication. CoRR abs/2410.21256 (2024) - 2023
- [j44]Jacob Browning, Yann LeCun:
Language, common sense, and the Winograd schema challenge. Artif. Intell. 325: 104031 (2023) - [j43]Yubei Chen, Adrien Bardes, Zengyi Li, Yann LeCun:
Bag of Image Patch Embedding Behind the Success of Self-Supervised Learning. Trans. Mach. Learn. Res. 2023 (2023) - [j42]Grégoire Mialon, Roberto Dessì, Maria Lomeli, Christoforos Nalmpantis, Ramakanth Pasunuru, Roberta Raileanu, Baptiste Rozière, Timo Schick, Jane Dwivedi-Yu, Asli Celikyilmaz, Edouard Grave, Yann LeCun, Thomas Scialom:
Augmented Language Models: a Survey. Trans. Mach. Learn. Res. 2023 (2023) - [j41]Shraman Pramanick, Li Jing, Sayan Nag, Jiachen Zhu, Hardik Shah, Yann LeCun, Rama Chellappa:
VoLTA: Vision-Language Transformer with Weakly-Supervised Local-Feature Alignment. Trans. Mach. Learn. Res. 2023 (2023) - [c176]Ying Wang, Jonas Pfeiffer, Nicolas Carion, Yann LeCun, Aishwarya Kamath:
Adapting Grounded Visual Question Answering Models to Low Resource Languages. CVPR Workshops 2023: 2596-2605 - [c175]Mahmoud Assran, Quentin Duval, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Michael G. Rabbat, Yann LeCun, Nicolas Ballas:
Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture. CVPR 2023: 15619-15629 - [c174]Randall Balestriero, Yann LeCun:
Fast and Exact Enumeration of Deep Networks Partitions Regions. ICASSP 2023: 1-5 - [c173]Randall Balestriero, Yann LeCun:
Police: Provably Optimal Linear Constraint Enforcement For Deep Neural Networks. ICASSP 2023: 1-5 - [c172]Vivien Cabannes, Léon Bottou, Yann LeCun, Randall Balestriero:
Active Self-Supervised Learning: A Few Low-Cost Relationships Are All You Need. ICCV 2023: 16228-16237 - [c171]Yubei Chen, Zeyu Yun, Yi Ma, Bruno A. Olshausen, Yann LeCun:
Minimalistic Unsupervised Representation Learning with the Sparse Manifold Transform. ICLR 2023 - [c170]Quentin Garrido, Yubei Chen, Adrien Bardes, Laurent Najman, Yann LeCun:
On the duality between contrastive and non-contrastive self-supervised learning. ICLR 2023 - [c169]Vivien Cabannes, Bobak Toussi Kiani, Randall Balestriero, Yann LeCun, Alberto Bietti:
The SSL Interplay: Augmentations, Inductive Bias, and Generalization. ICML 2023: 3252-3298 - [c168]Quentin Garrido, Randall Balestriero, Laurent Najman, Yann LeCun:
RankMe: Assessing the Downstream Performance of Pretrained Self-Supervised Representations by Their Rank. ICML 2023: 10929-10974 - [c167]Quentin Garrido, Laurent Najman, Yann LeCun:
Self-supervised learning of Split Invariant Equivariant representations. ICML 2023: 10975-10996 - [c166]Xiaoxin He, Bryan Hooi, Thomas Laurent, Adam Perold, Yann LeCun, Xavier Bresson:
A Generalization of ViT/MLP-Mixer to Graphs. ICML 2023: 12724-12745 - [c165]Ido Ben-Shaul, Ravid Shwartz-Ziv, Tomer Galanti, Shai Dekel, Yann LeCun:
Reverse Engineering Self-Supervised Learning. NeurIPS 2023 - [c164]Grégoire Mialon, Quentin Garrido, Hannah Lawrence, Danyal Rehman, Yann LeCun, Bobak T. Kiani:
Self-Supervised Learning with Lie Symmetries for Partial Differential Equations. NeurIPS 2023 - [c163]Ravid Shwartz-Ziv, Randall Balestriero, Kenji Kawaguchi, Tim G. J. Rudner, Yann LeCun:
An Information Theory Perspective on Variance-Invariance-Covariance Regularization. NeurIPS 2023 - [c162]Jiayun Wang, Yubei Chen, Stella X. Yu, Brian Cheung, Yann LeCun:
Compact and Optimal Deep Learning with Recurrent Parameter Generators. WACV 2023: 3889-3899 - [i121]Mahmoud Assran, Quentin Duval, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Michael G. Rabbat, Yann LeCun, Nicolas Ballas:
Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture. CoRR abs/2301.08243 (2023) - [i120]Shoaib Ahmed Siddiqui, David Krueger, Yann LeCun, Stéphane Deny:
Blockwise Self-Supervised Learning at Scale. CoRR abs/2302.01647 (2023) - [i119]Vivien Cabannes, Bobak Toussi Kiani, Randall Balestriero, Yann LeCun, Alberto Bietti:
The SSL Interplay: Augmentations, Inductive Bias, and Generalization. CoRR abs/2302.02774 (2023) - [i118]Grégoire Mialon, Roberto Dessì, Maria Lomeli, Christoforos Nalmpantis, Ramakanth Pasunuru, Roberta Raileanu, Baptiste Rozière, Timo Schick, Jane Dwivedi-Yu, Asli Celikyilmaz, Edouard Grave, Yann LeCun, Thomas Scialom:
Augmented Language Models: a Survey. CoRR abs/2302.07842 (2023) - [i117]Quentin Garrido, Laurent Najman, Yann LeCun:
Self-supervised learning of Split Invariant Equivariant representations. CoRR abs/2302.10283 (2023) - [i116]Ravid Shwartz-Ziv, Randall Balestriero, Kenji Kawaguchi, Tim G. J. Rudner, Yann LeCun:
An Information-Theoretic Perspective on Variance-Invariance-Covariance Regularization. CoRR abs/2303.00633 (2023) - [i115]Vivien Cabannes, Léon Bottou, Yann LeCun, Randall Balestriero:
Active Self-Supervised Learning: A Few Low-Cost Relationships Are All You Need. CoRR abs/2303.15256 (2023) - [i114]Shengbang Tong, Yubei Chen, Yi Ma, Yann LeCun:
EMP-SSL: Towards Self-Supervised Learning in One Training Epoch. CoRR abs/2304.03977 (2023) - [i113]Ravid Shwartz-Ziv, Yann LeCun:
To Compress or Not to Compress - Self-Supervised Learning and Information Theory: A Review. CoRR abs/2304.09355 (2023) - [i112]Randall Balestriero, Mark Ibrahim, Vlad Sobal, Ari Morcos, Shashank Shekhar, Tom Goldstein, Florian Bordes, Adrien Bardes, Grégoire Mialon, Yuandong Tian, Avi Schwarzschild, Andrew Gordon Wilson, Jonas Geiping, Quentin Garrido, Pierre Fernandez, Amir Bar, Hamed Pirsiavash, Yann LeCun, Micah Goldblum:
A Cookbook of Self-Supervised Learning. CoRR abs/2304.12210 (2023) - [i111]Ido Ben-Shaul, Ravid Shwartz-Ziv, Tomer Galanti, Shai Dekel, Yann LeCun:
Reverse Engineering Self-Supervised Learning. CoRR abs/2305.15614 (2023) - [i110]Anna Dawid, Yann LeCun:
Introduction to Latent Variable Energy-Based Models: A Path Towards Autonomous Machine Intelligence. CoRR abs/2306.02572 (2023) - [i109]Jiachen Zhu, Ravid Shwartz-Ziv, Yubei Chen, Yann LeCun:
Variance-Covariance Regularization Improves Representation Learning. CoRR abs/2306.13292 (2023) - [i108]Grégoire Mialon, Quentin Garrido, Hannah Lawrence, Danyal Rehman, Yann LeCun, Bobak Toussi Kiani:
Self-Supervised Learning with Lie Symmetries for Partial Differential Equations. CoRR abs/2307.05432 (2023) - [i107]Adrien Bardes, Jean Ponce, Yann LeCun:
MC-JEPA: A Joint-Embedding Predictive Architecture for Self-Supervised Learning of Motion and Content Features. CoRR abs/2307.12698 (2023) - [i106]Amir Bar, Florian Bordes, Assaf Shocher, Mahmoud Assran, Pascal Vincent, Nicolas Ballas, Trevor Darrell, Amir Globerson, Yann LeCun:
Predicting masked tokens in stochastic locations improves masked image modeling. CoRR abs/2308.00566 (2023) - [i105]Zeyu Yun, Juexiao Zhang, Bruno A. Olshausen, Yann LeCun, Yubei Chen:
URLOST: Unsupervised Representation Learning without Stationarity or Topology. CoRR abs/2310.04496 (2023) - [i104]Grégoire Mialon, Clémentine Fourrier, Craig Swift, Thomas Wolf, Yann LeCun, Thomas Scialom:
GAIA: a benchmark for General AI Assistants. CoRR abs/2311.12983 (2023) - [i103]Jyothir S. V, Siddhartha Jalagam, Yann LeCun, Vlad Sobal:
Gradient-based Planning with World Models. CoRR abs/2312.17227 (2023) - 2022
- [j40]Yutaka Matsuo, Yann LeCun, Maneesh Sahani, Doina Precup, David Silver, Masashi Sugiyama, Eiji Uchibe, Jun Morimoto:
Deep learning, reinforcement learning, and world models. Neural Networks 152: 267-275 (2022) - [j39]Katrina Evtimova, Yann LeCun:
Sparse Coding with Multi-layer Decoders using Variance Regularization. Trans. Mach. Learn. Res. 2022 (2022) - [c161]Chun-Hsiao Yeh, Cheng-Yao Hong, Yen-Chi Hsu, Tyng-Luh Liu, Yubei Chen, Yann LeCun:
Decoupled Contrastive Learning. ECCV (26) 2022: 668-684 - [c160]Adrien Bardes, Jean Ponce, Yann LeCun:
VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning. ICLR 2022 - [c159]Li Jing, Pascal Vincent, Yann LeCun, Yuandong Tian:
Understanding Dimensional Collapse in Contrastive Self-supervised Learning. ICLR 2022 - [c158]Randall Balestriero, Léon Bottou, Yann LeCun:
The Effects of Regularization and Data Augmentation are Class Dependent. NeurIPS 2022 - [c157]Randall Balestriero, Yann LeCun:
Contrastive and Non-Contrastive Self-Supervised Learning Recover Global and Local Spectral Embedding Methods. NeurIPS 2022 - [c156]Randall Balestriero, Ishan Misra, Yann LeCun:
A Data-Augmentation Is Worth A Thousand Samples: Analytical Moments And Sampling-Free Training. NeurIPS 2022 - [c155]Adrien Bardes, Jean Ponce, Yann LeCun:
VICRegL: Self-Supervised Learning of Local Visual Features. NeurIPS 2022 - [c154]Zi-Yi Dou, Aishwarya Kamath, Zhe Gan, Pengchuan Zhang, Jianfeng Wang, Linjie Li, Zicheng Liu, Ce Liu, Yann LeCun, Nanyun Peng, Jianfeng Gao, Lijuan Wang:
Coarse-to-Fine Vision-Language Pre-training with Fusion in the Backbone. NeurIPS 2022 - [c153]Bobak Toussi Kiani, Randall Balestriero, Yann LeCun, Seth Lloyd:
projUNN: efficient method for training deep networks with unitary matrices. NeurIPS 2022 - [c152]Ravid Shwartz-Ziv, Micah Goldblum, Hossein Souri, Sanyam Kapoor, Chen Zhu, Yann LeCun, Andrew Gordon Wilson:
Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors. NeurIPS 2022 - [i102]Zengyi Li, Yubei Chen, Yann LeCun, Friedrich T. Sommer:
Neural Manifold Clustering and Embedding. CoRR abs/2201.10000 (2022) - [i101]Randall Balestriero, Ishan Misra, Yann LeCun:
A Data-Augmentation Is Worth A Thousand Samples: Exact Quantification From Analytical Augmented Sample Moments. CoRR abs/2202.08325 (2022) - [i100]Bobak Toussi Kiani, Randall Balestriero, Yann LeCun, Seth Lloyd:
projUNN: efficient method for training deep networks with unitary matrices. CoRR abs/2203.05483 (2022) - [i99]Randall Balestriero, Léon Bottou, Yann LeCun:
The Effects of Regularization and Data Augmentation are Class Dependent. CoRR abs/2204.03632 (2022) - [i98]Vlad Sobal, Alfredo Canziani, Nicolas Carion, Kyunghyun Cho, Yann LeCun:
Separating the World and Ego Models for Self-Driving. CoRR abs/2204.07184 (2022) - [i97]Ravid Shwartz-Ziv, Micah Goldblum, Hossein Souri, Sanyam Kapoor, Chen Zhu, Yann LeCun, Andrew Gordon Wilson:
Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors. CoRR abs/2205.10279 (2022) - [i96]Randall Balestriero, Yann LeCun:
Contrastive and Non-Contrastive Self-Supervised Learning Recover Global and Local Spectral Embedding Methods. CoRR abs/2205.11508 (2022) - [i95]Quentin Garrido, Yubei Chen, Adrien Bardes, Laurent Najman, Yann LeCun:
On the duality between contrastive and non-contrastive self-supervised learning. CoRR abs/2206.02574 (2022) - [i94]Zi-Yi Dou, Aishwarya Kamath, Zhe Gan, Pengchuan Zhang, Jianfeng Wang, Linjie Li, Zicheng Liu, Ce Liu, Yann LeCun, Nanyun Peng, Jianfeng Gao, Lijuan Wang:
Coarse-to-Fine Vision-Language Pre-training with Fusion in the Backbone. CoRR abs/2206.07643 (2022) - [i93]Li Jing, Jiachen Zhu, Yann LeCun:
Masked Siamese ConvNets. CoRR abs/2206.07700 (2022) - [i92]Yubei Chen, Adrien Bardes, Zengyi Li, Yann LeCun:
Intra-Instance VICReg: Bag of Self-Supervised Image Patch Embedding. CoRR abs/2206.08954 (2022) - [i91]Jiachen Zhu, Rafael M. Moraes, Serkan Karakulak, Vlad Sobol, Alfredo Canziani, Yann LeCun:
TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning. CoRR abs/2206.10698 (2022) - [i90]Ravid Shwartz-Ziv, Randall Balestriero, Yann LeCun:
What Do We Maximize in Self-Supervised Learning? CoRR abs/2207.10081 (2022) - [i89]Wancong Zhang, Anthony GX-Chen, Vlad Sobal, Yann LeCun, Nicolas Carion:
Light-weight probing of unsupervised representations for Reinforcement Learning. CoRR abs/2208.12345 (2022) - [i88]Bobak Toussi Kiani, Randall Balestriero, Yubei Chen, Seth Lloyd, Yann LeCun:
Joint Embedding Self-Supervised Learning in the Kernel Regime. CoRR abs/2209.14884 (2022) - [i87]Grégoire Mialon, Randall Balestriero, Yann LeCun:
Variance Covariance Regularization Enforces Pairwise Independence in Self-Supervised Representations. CoRR abs/2209.14905 (2022) - [i86]Yubei Chen, Zeyu Yun, Yi Ma, Bruno A. Olshausen, Yann LeCun:
Minimalistic Unsupervised Learning with the Sparse Manifold Transform. CoRR abs/2209.15261 (2022) - [i85]Adrien Bardes, Jean Ponce, Yann LeCun:
VICRegL: Self-Supervised Learning of Local Visual Features. CoRR abs/2210.01571 (2022) - [i84]Quentin Garrido, Randall Balestriero, Laurent Najman, Yann LeCun:
RankMe: Assessing the downstream performance of pretrained self-supervised representations by their rank. CoRR abs/2210.02885 (2022) - [i83]Shraman Pramanick, Li Jing, Sayan Nag, Jiachen Zhu, Hardik Shah, Yann LeCun, Rama Chellappa:
VoLTA: Vision-Language Transformer with Weakly-Supervised Local-Feature Alignment. CoRR abs/2210.04135 (2022) - [i82]Anthony Zador, Blake A. Richards, Bence Ölveczky, Sean Escola, Yoshua Bengio, Kwabena Boahen, Matthew M. Botvinick, Dmitri B. Chklovskii, Anne Churchland, Claudia Clopath, James DiCarlo, Surya Ganguli, Jeff Hawkins, Konrad P. Körding, Alexei A. Koulakov, Yann LeCun, Timothy P. Lillicrap, Adam H. Marblestone, Bruno A. Olshausen, Alexandre Pouget, Cristina Savin, Terrence J. Sejnowski, Eero P. Simoncelli, Sara A. Solla, David Sussillo, Andreas S. Tolias, Doris Tsao:
Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution. CoRR abs/2210.08340 (2022) - [i81]Shengbang Tong, Xili Dai, Yubei Chen, Mingyang Li, Zengyi Li, Brent Yi, Yann LeCun, Yi Ma:
Unsupervised Learning of Structured Representations via Closed-Loop Transcription. CoRR abs/2210.16782 (2022) - [i80]Randall Balestriero, Yann LeCun:
POLICE: Provably Optimal Linear Constraint Enforcement for Deep Neural Networks. CoRR abs/2211.01340 (2022) - [i79]Vlad Sobal, Jyothir S. V, Siddhartha Jalagam, Nicolas Carion, Kyunghyun Cho, Yann LeCun:
Joint Embedding Predictive Architectures Focus on Slow Features. CoRR abs/2211.10831 (2022) - [i78]Xiaoxin He, Bryan Hooi, Thomas Laurent, Adam Perold, Yann LeCun, Xavier Bresson:
A Generalization of ViT/MLP-Mixer to Graphs. CoRR abs/2212.13350 (2022) - 2021
- [j38]Yoshua Bengio, Yann LeCun, Geoffrey E. Hinton:
Deep learning for AI. Commun. ACM 64(7): 58-65 (2021) - [j37]Baptiste Rozière, Morgane Rivière, Olivier Teytaud, Jérémy Rapin, Yann LeCun, Camille Couprie:
Inspirational Adversarial Image Generation. IEEE Trans. Image Process. 30: 4036-4045 (2021) - [c151]Zeyu Yun, Yubei Chen, Bruno A. Olshausen, Yann LeCun:
Transformer visualization via dictionary learning: contextualized embedding as a linear superposition of transformer factors. DeeLIO@NAACL-HLT 2021: 1-10 - [c150]Aishwarya Kamath, Mannat Singh, Yann LeCun, Gabriel Synnaeve, Ishan Misra, Nicolas Carion:
MDETR - Modulated Detection for End-to-End Multi-Modal Understanding. ICCV 2021: 1760-1770 - [c149]Jure Zbontar, Li Jing, Ishan Misra, Yann LeCun, Stéphane Deny:
Barlow Twins: Self-Supervised Learning via Redundancy Reduction. ICML 2021: 12310-12320 - [d1]Xiang Zhang, Junbo Zhao, Yann LeCun:
DBPedia. IEEE DataPort, 2021
- [i77]Jure Zbontar, Li Jing, Ishan Misra, Yann LeCun, Stéphane Deny:
Barlow Twins: Self-Supervised Learning via Redundancy Reduction. CoRR abs/2103.03230 (2021) - [i76]