Razvan Pascanu
Razvan Pascanu
Research Scientist at Google DeepMind
Verified email at google.com - Homepage
Title
Cited by
Cited by
Year
On the difficulty of training recurrent neural networks
R Pascanu, T Mikolov, Y Bengio
International conference on machine learning, 1310-1318, 2013
38982013
Theano: a CPU and GPU math expression compiler
J Bergstra, O Breuleux, F Bastien, P Lamblin, R Pascanu, G Desjardins, ...
Proceedings of the Python for scientific computing conference (SciPy) 4 (3), 1-7, 2010
18612010
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
18352017
Theano: new features and speed improvements
F Bastien, P Lamblin, R Pascanu, J Bergstra, I Goodfellow, A Bergeron, ...
arXiv preprint arXiv:1211.5590, 2012
15472012
Identifying and attacking the saddle point problem in high-dimensional non-convex optimization
Y Dauphin, R Pascanu, C Gulcehre, K Cho, S Ganguli, Y Bengio
arXiv preprint arXiv:1406.2572, 2014
11352014
Relational inductive biases, deep learning, and graph networks
PW Battaglia, JB Hamrick, V Bapst, A Sanchez-Gonzalez, V Zambaldi, ...
arXiv preprint arXiv:1806.01261, 2018
11242018
Progressive neural networks
AA Rusu, NC Rabinowitz, G Desjardins, H Soyer, J Kirkpatrick, ...
arXiv preprint arXiv:1606.04671, 2016
9892016
A simple neural network module for relational reasoning
A Santoro, D Raposo, DGT Barrett, M Malinowski, R Pascanu, P Battaglia, ...
arXiv preprint arXiv:1706.01427, 2017
9782017
On the number of linear regions of deep neural networks
G Montúfar, R Pascanu, K Cho, Y Bengio
arXiv preprint arXiv:1402.1869, 2014
8702014
How to construct deep recurrent neural networks
R Pascanu, C Gulcehre, K Cho, Y Bengio
arXiv preprint arXiv:1312.6026, 2013
8332013
Theano: A CPU and GPU math compiler in Python
J Bergstra, O Breuleux, F Bastien, P Lamblin, R Pascanu, G Desjardins, ...
Proc. 9th Python in Science Conf 1, 3-10, 2010
7282010
Interaction networks for learning about objects, relations and physics
PW Battaglia, R Pascanu, M Lai, D Rezende, K Kavukcuoglu
arXiv preprint arXiv:1612.00222, 2016
6872016
Theano: A Python framework for fast computation of mathematical expressions
R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, N Ballas, ...
arXiv e-prints, arXiv: 1605.02688, 2016
6212016
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
5532016
Advances in optimizing recurrent networks
Y Bengio, N Boulanger-Lewandowski, R Pascanu
2013 IEEE International Conference on Acoustics, Speech and Signal …, 2013
5042013
Understanding the exploding gradient problem
R Pascanu, T Mikolov, Y Bengio
CoRR, abs/1211.5063 2 (417), 1, 2012
4752012
Meta-learning with latent embedding optimization
AA Rusu, D Rao, J Sygnowski, O Vinyals, R Pascanu, S Osindero, ...
arXiv preprint arXiv:1807.05960, 2018
4542018
Imagination-augmented agents for deep reinforcement learning
S Racanière, T Weber, DP Reichert, L Buesing, A Guez, D Rezende, ...
Proceedings of the 31st International Conference on Neural Information …, 2017
384*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
3472017
Sharp minima can generalize for deep nets
L Dinh, R Pascanu, S Bengio, Y Bengio
International Conference on Machine Learning, 1019-1028, 2017
3352017
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Articles 1–20