Raia Hadsell
Raia Hadsell
Google DeepMind
Verified email at google.com - Homepage
Cited by
Cited by
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
Dimensionality reduction by learning an invariant mapping
R Hadsell, S Chopra, Y LeCun
2006 IEEE Computer Society Conference on Computer Vision and Pattern …, 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
Progressive neural networks
AA Rusu, NC Rabinowitz, G Desjardins, H Soyer, J Kirkpatrick, ...
arXiv preprint arXiv:1606.04671, 2016
A tutorial on energy-based learning
Y LeCun, S Chopra, R Hadsell, M Ranzato, F Huang
Predicting structured data 1 (0), 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
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
Meta-learning with latent embedding optimization
AA Rusu, D Rao, J Sygnowski, O Vinyals, R Pascanu, S Osindero, ...
arXiv preprint arXiv:1807.05960, 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
Policy distillation
AA Rusu, SG Colmenarejo, C Gulcehre, G Desjardins, J Kirkpatrick, ...
arXiv preprint arXiv:1511.06295, 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
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, 4496-4506, 2017
Progress & compress: A scalable framework for continual learning
J Schwarz, J Luketina, WM Czarnecki, A Grabska-Barwinska, YW Teh, ...
arXiv preprint arXiv:1805.06370, 2018
Graph networks as learnable physics engines for inference and control
A Sanchez-Gonzalez, N Heess, JT Springenberg, J Merel, M Riedmiller, ...
arXiv preprint arXiv:1806.01242, 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
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
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, 2419-2430, 2018
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 Conference on Computer Vision and Pattern …, 2019
Improved global routing through congestion estimation
RT Hadsell, PH Madden
Proceedings 2003. Design Automation Conference (IEEE Cat. No. 03CH37451), 28-31, 2003
Deep belief net learning in a long-range vision system for autonomous off-road driving
R Hadsell, A Erkan, P Sermanet, M Scoffier, U Muller, Y LeCun
2008 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2008
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