| Dimensionality reduction by learning an invariant mapping R Hadsell, S Chopra, Y LeCun 2006 IEEE Computer Society Conference on Computer Vision and Pattern …, 2006 | 4775 | 2006 |
| 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 | 4666 | 2017 |
| 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 | 4462 | 2005 |
| Progressive neural networks AA Rusu, NC Rabinowitz, G Desjardins, H Soyer, J Kirkpatrick, ... arXiv preprint arXiv:1606.04671, 2016 | 2086 | 2016 |
| Meta-learning with latent embedding optimization AA Rusu, D Rao, J Sygnowski, O Vinyals, R Pascanu, S Osindero, ... arXiv preprint arXiv:1807.05960, 2018 | 1227 | 2018 |
| A tutorial on energy-based learning Y LeCun, S Chopra, R Hadsell, M Ranzato, F Huang Predicting structured data 1 (0), 2006 | 1208 | 2006 |
| 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 | 838 | 2016 |
| 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 | 625 | 2018 |
| Policy distillation AA Rusu, SG Colmenarejo, C Gulcehre, G Desjardins, J Kirkpatrick, ... arXiv preprint arXiv:1511.06295, 2015 | 596 | 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 | 572 | 2018 |
| 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 | 556 | 2017 |
| 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 | 554 | 2018 |
| 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 | 501 | 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 | 500 | 2017 |
| Learning long‐range vision for autonomous off‐road driving R Hadsell, P Sermanet, J Ben, A Erkan, M Scoffier, K Kavukcuoglu, ... Journal of Field Robotics 26 (2), 120-144, 2009 | 435 | 2009 |
| 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 | 410 | 2019 |
| 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 | 334 | 2021 |
| Reinforcement and imitation learning for diverse visuomotor skills Y Zhu, Z Wang, J Merel, A Rusu, T Erez, S Cabi, S Tunyasuvunakool, ... arXiv preprint arXiv:1802.09564, 2018 | 292 | 2018 |
| Learning to navigate in cities without a map P Mirowski, M Grimes, M Malinowski, KM Hermann, K Anderson, ... Advances in neural information processing systems 31, 2018 | 277 | 2018 |
| A generalist agent S Reed, K Zolna, E Parisotto, SG Colmenarejo, A Novikov, G Barth-Maron, ... arXiv preprint arXiv:2205.06175, 2022 | 266 | 2022 |
Razvan PascanuResearch Scientist at Google DeepMindVerified email at google.com
