Razvan Pascanu
TítuloCitado porAno
On the difficulty of training recurrent neural networks
R Pascanu, T Mikolov, Y Bengio
International conference on machine learning, 1310-1318, 2013
26652013
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), 2010
16772010
Theano: new features and speed improvements
F Bastien, P Lamblin, R Pascanu, J Bergstra, I Goodfellow, A Bergeron, ...
arXiv preprint arXiv:1211.5590, 2012
13682012
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
8712017
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, 2933-2941, 2014
8402014
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
6232010
How to construct deep recurrent neural networks
R Pascanu, C Gulcehre, K Cho, Y Bengio
arXiv preprint arXiv:1312.6026, 2013
5882013
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
5752014
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
5632017
Progressive neural networks
AA Rusu, NC Rabinowitz, G Desjardins, H Soyer, J Kirkpatrick, ...
arXiv preprint arXiv:1606.04671, 2016
5532016
Theano: A Python framework for fast computation of mathematical expressions
R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, N Ballas, ...
arXiv preprint arXiv:1605.02688, 2016
5032016
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
4392018
Advances in optimizing recurrent networks
Y Bengio, N Boulanger-Lewandowski, R Pascanu
2013 IEEE International Conference on Acoustics, Speech and Signal …, 2013
3932013
Interaction networks for learning about objects, relations and physics
P Battaglia, R Pascanu, M Lai, DJ Rezende
Advances in neural information processing systems, 4502-4510, 2016
3912016
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
3552016
Understanding the exploding gradient problem
R Pascanu, T Mikolov, Y Bengio
CoRR, abs/1211.5063 2, 417, 2012
3012012
Pylearn2: a machine learning research library
IJ Goodfellow, D Warde-Farley, P Lamblin, V Dumoulin, M Mirza, ...
arXiv preprint arXiv:1308.4214, 2013
2902013
Combining modality specific deep neural networks for emotion recognition in video
SE Kahou, C Pal, X Bouthillier, P Froumenty, Ç Gülçehre, R Memisevic, ...
Proceedings of the 15th ACM on International conference on multimodal …, 2013
2412013
Theano: Deep learning on gpus with python
J Bergstra, F Bastien, O Breuleux, P Lamblin, R Pascanu, O Delalleau, ...
NIPS 2011, BigLearning Workshop, Granada, Spain 3, 1-48, 2011
2402011
Sim-to-real robot learning from pixels with progressive nets
AA Rusu, M Vecerik, T Rothörl, N Heess, R Pascanu, R Hadsell
arXiv preprint arXiv:1610.04286, 2016
2382016
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