| Overcoming catastrophic forgetting in neural networks J Kirkpatrick, R Pascanu, N Rabinowitz, J Veness, G Desjardins, AA Rusu, ... Proceedings of the national academy of sciences 114 (13), 3521-3526, 2017 | 11403 | 2017 |
| Dimensionality reduction by learning an invariant mapping R Hadsell, S Chopra, Y LeCun 2006 IEEE computer society conference on computer vision and pattern …, 2006 | 7535 | 2006 |
| Learning a similarity metric discriminatively, with application to face verification S Chopra, R Hadsell, Y LeCun 2005 IEEE computer society conference on computer vision and pattern …, 2005 | 6148 | 2005 |
| Progressive neural networks AA Rusu, NC Rabinowitz, G Desjardins, H Soyer, J Kirkpatrick, ... arXiv preprint arXiv:1606.04671, 2016 | 3894 | 2016 |
| A tutorial on energy-based learning Y LeCun, S Chopra, R Hadsell, M Ranzato, F Huang Predicting structured data 1 (0), 2006 | 2262 | 2006 |
| Meta-learning with latent embedding optimization AA Rusu, D Rao, J Sygnowski, O Vinyals, R Pascanu, S Osindero, ... arXiv preprint arXiv:1807.05960, 2018 | 1879 | 2018 |
| Gemma 2: Improving open language models at a practical size G Team, M Riviere, S Pathak, PG Sessa, C Hardin, S Bhupatiraju, ... arXiv preprint arXiv:2408.00118, 2024 | 1691 | 2024 |
| A generalist agent S Reed, K Zolna, E Parisotto, SG Colmenarejo, A Novikov, G Barth-Maron, ... arXiv preprint arXiv:2205.06175, 2022 | 1430 | 2022 |
| Gemini 2.5: Pushing the frontier with advanced reasoning, multimodality, long context, and next generation agentic capabilities G Comanici, E Bieber, M Schaekermann, I Pasupat, N Sachdeva, I Dhillon, ... arXiv preprint arXiv:2507.06261, 2025 | 1337 | 2025 |
| Progress & compress: A scalable framework for continual learning J Schwarz, W Czarnecki, J Luketina, A Grabska-Barwinska, YW Teh, ... International conference on machine learning, 4528-4537, 2018 | 1212 | 2018 |
| Skilful precipitation nowcasting using deep generative models of radar S Ravuri, K Lenc, M Willson, D Kangin, R Lam, P Mirowski, M Fitzsimons, ... Nature 597 (7878), 672-677, 2021 | 1172 | 2021 |
| Learning to navigate in complex environments P Mirowski, R Pascanu, F Viola, H Soyer, AJ Ballard, A Banino, M Denil, ... arXiv preprint arXiv:1611.03673, 2016 | 1140 | 2016 |
| Policy distillation AA Rusu, SG Colmenarejo, C Gulcehre, G Desjardins, J Kirkpatrick, ... arXiv preprint arXiv:1511.06295, 2015 | 1005 | 2015 |
| Vector-based navigation using grid-like representations in artificial agents A Banino, C Barry, B Uria, C Blundell, T Lillicrap, P Mirowski, A Pritzel, ... Nature 557 (7705), 429-433, 2018 | 934 | 2018 |
| Graph networks as learnable physics engines for inference and control A Sanchez-Gonzalez, N Heess, JT Springenberg, J Merel, M Riedmiller, ... International conference on machine learning, 4470-4479, 2018 | 859 | 2018 |
| Embracing change: Continual learning in deep neural networks R Hadsell, D Rao, AA Rusu, R Pascanu Trends in cognitive sciences 24 (12), 1028-1040, 2020 | 805 | 2020 |
| The limits and potentials of deep learning for robotics N Sünderhauf, O Brock, W Scheirer, R Hadsell, D Fox, J Leitner, B Upcroft, ... The International journal of robotics research 37 (4-5), 405-420, 2018 | 756 | 2018 |
| Distral: Robust multitask reinforcement learning Y Teh, V Bapst, WM Czarnecki, J Quan, J Kirkpatrick, R Hadsell, N Heess, ... Advances in neural information processing systems 30, 2017 | 730 | 2017 |
| Sim-to-real robot learning from pixels with progressive nets AA Rusu, M Večerík, T Rothörl, N Heess, R Pascanu, R Hadsell Conference on robot learning, 262-270, 2017 | 718 | 2017 |
| Sim-to-real via sim-to-sim: Data-efficient robotic grasping via randomized-to-canonical adaptation networks S James, P Wohlhart, M Kalakrishnan, D Kalashnikov, A Irpan, J Ibarz, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 651 | 2019 |
Yann LeCunChief AI Scientist at Facebook & JT Schwarz Professor at the Courant Institute, New York UniversityVerified email at cs.nyu.edu
