Razvan Pascanu
Razvan Pascanu
Research Scientist at Google DeepMind
Adresse e-mail validée de google.com - Page d'accueil
Citée par
Citée par
On the difficulty of training recurrent neural networks
R Pascanu, T Mikolov, Y Bengio
International conference on machine learning, 1310-1318, 2013
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
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
Theano: new features and speed improvements
F Bastien, P Lamblin, R Pascanu, J Bergstra, I Goodfellow, A Bergeron, ...
arXiv preprint arXiv:1211.5590, 2012
Identifying and attacking the saddle point problem in high-dimensional non-convex optimization
YN Dauphin, R Pascanu, C Gulcehre, K Cho, S Ganguli, Y Bengio
Advances in neural information processing systems 27, 2933-2941, 2014
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
A simple neural network module for relational reasoning
A Santoro, D Raposo, DG Barrett, M Malinowski, R Pascanu, P Battaglia, ...
Advances in neural information processing systems, 4967-4976, 2017
Progressive neural networks
AA Rusu, NC Rabinowitz, G Desjardins, H Soyer, J Kirkpatrick, ...
arXiv preprint arXiv:1606.04671, 2016
On the number of linear regions of deep neural networks
GF Montufar, R Pascanu, K Cho, Y Bengio
Advances in neural information processing systems, 2924-2932, 2014
How to construct deep recurrent neural networks
R Pascanu, C Gulcehre, K Cho, Y Bengio
arXiv preprint arXiv:1312.6026, 2013
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
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
Theano: A Python framework for fast computation of mathematical expressions
R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, N Ballas, ...
arXiv, arXiv: 1605.02688, 2016
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
Advances in optimizing recurrent networks
Y Bengio, N Boulanger-Lewandowski, R Pascanu
2013 IEEE International Conference on Acoustics, Speech and Signal …, 2013
Understanding the exploding gradient problem
R Pascanu, T Mikolov, Y Bengio
CoRR, abs/1211.5063 2, 417, 2012
Meta-learning with latent embedding optimization
AA Rusu, D Rao, J Sygnowski, O Vinyals, R Pascanu, S Osindero, ...
arXiv preprint arXiv:1807.05960, 2018
Imagination-augmented agents for deep reinforcement learning
S Racanière, T Weber, D Reichert, L Buesing, A Guez, DJ Rezende, ...
Advances in neural information processing systems, 5690-5701, 2017
Pylearn2: a machine learning research library
IJ Goodfellow, D Warde-Farley, P Lamblin, V Dumoulin, M Mirza, ...
arXiv preprint arXiv:1308.4214, 2013
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
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