Guillaume Alain

19 papers A* 2Journal 12Unranked 5

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Introducing Milabench: Benchmarking Accelerators for AI. CoRR Pierre Delaunay, Xavier Bouthillier, Olivier Breuleux, Satya Ortiz-Gagné, Olexa Bilaniuk, Fabrice Normandin, Arnaud Bergeron, Bruno Carrez, Guillaume Alain, Soline Blanc, Frédéric Osterrath, Joseph Viviano, Roger Creus-Castanyer Darshan Patil, Rabiul Awal, Le Zhang
2020	—	`conf`	DeepDrummer : Generating Drum Loops using Deep Learning and a Human in the Loop. AIMC Guillaume Alain, Maxime Chevalier-Boisvert, Frédéric Osterrath, Rémi Piché-Taillefer
2020	J	`jnl`	DeepDrummer : Generating Drum Loops using Deep Learning and a Human in the Loop. CoRR Guillaume Alain, Maxime Chevalier-Boisvert, Frédéric Osterrath, Rémi Piché-Taillefer
2019	J	`jnl`	Negative eigenvalues of the Hessian in deep neural networks. CoRR Guillaume Alain, Nicolas Le Roux, Pierre-Antoine Manzagol
2019	J	`jnl`	Robo-PlaNet: Learning to Poke in a Day. CoRR Maxime Chevalier-Boisvert, Guillaume Alain, Florian Golemo, Derek Nowrouzezahrai
2018	—	`conf`	Negative eigenvalues of the Hessian in deep neural networks. ICLR (Workshop) Guillaume Alain, Nicolas Le Roux, Pierre-Antoine Manzagol
2017	—	`conf`	Understanding intermediate layers using linear classifier probes. ICLR (Workshop) Guillaume Alain, Yoshua Bengio
2016	J	`jnl`	Theano: A Python framework for fast computation of mathematical expressions. CoRR Rami Al-Rfou, Guillaume Alain, Amjad Almahairi, Christof Angermüller, Dzmitry Bahdanau, Nicolas Ballas, Frédéric Bastien, Justin Bayer, Anatoly Belikov, Alexander Belopolsky, Yoshua Bengio, Arnaud Bergeron, James Bergstra, Valentin Bisson, Josh Bleecher Snyder, Nicolas Bouchard, Nicolas Boulanger-Lewandowski, Xavier Bouthillier, Alexandre de Brébisson, Olivier Breuleux, Pierre Luc Carrier, Kyunghyun Cho, Jan Chorowski, Paul F. Christiano, Tim Cooijmans, Marc-Alexandre Côté, Myriam Côté, Aaron C. Courville, Yann N. Dauphin, Olivier Delalleau, Julien Demouth, Guillaume Desjardins, Sander Dieleman, Laurent Dinh, Melanie Ducoffe, Vincent Dumoulin, Samira Ebrahimi Kahou, Dumitru Erhan, Ziye Fan, Orhan Firat, Mathieu Germain, Xavier Glorot, Ian J. Goodfellow, Matthew Graham, Çaglar Gülçehre, Philippe Hamel, Iban Harlouchet, Jean-Philippe Heng, Balázs Hidasi, Sina Honari, Arjun Jain, Sébastien Jean, Kai Jia, Mikhail Korobov, Vivek Kulkarni, Alex Lamb, Pascal Lamblin, Eric Larsen, César Laurent, Sean Lee, Simon Lefrançois, Simon Lemieux, Nicholas Léonard, Zhouhan Lin, Jesse A. Livezey, Cory Lorenz, Jeremiah Lowin, Qianli Ma, Pierre-Antoine Manzagol, Olivier Mastropietro, Robert McGibbon, Roland Memisevic, Bart van Merriënboer, Vincent Michalski, Mehdi Mirza, Alberto Orlandi, Christopher Joseph Pal, Razvan Pascanu, Mohammad Pezeshki, Colin Raffel, Daniel Renshaw, Matthew Rocklin, Adriana Romero, Markus Roth, Peter Sadowski, John Salvatier, François Savard, Jan Schlüter, John Schulman, Gabriel Schwartz, Iulian Vlad Serban, Dmitriy Serdyuk, Samira Shabanian, Étienne Simon, Sigurd Spieckermann, S. Ramana Subramanyam, Jakub Sygnowski, Jérémie Tanguay, Gijs van Tulder, Joseph P. Turian, Sebastian Urban, Pascal Vincent, Francesco Visin, Harm de Vries, David Warde-Farley, Dustin J. Webb, Matthew Willson, Kelvin Xu, Lijun Xue, Li Yao, Saizheng Zhang, Ying Zhang
2016	J	`jnl`	Understanding intermediate layers using linear classifier probes. CoRR Guillaume Alain, Yoshua Bengio
2015	J	`jnl`	GSNs : Generative Stochastic Networks. CoRR Guillaume Alain, Yoshua Bengio, Li Yao, Jason Yosinski, Eric Thibodeau-Laufer, Saizheng Zhang, Pascal Vincent
2015	—	`conf`	Techniques for Learning Binary Stochastic Feedforward Neural Networks. ICLR (Poster) Tapani Raiko, Mathias Berglund, Guillaume Alain, Laurent Dinh
2015	J	`jnl`	Variance Reduction in SGD by Distributed Importance Sampling. CoRR Guillaume Alain, Alex Lamb, Chinnadhurai Sankar, Aaron C. Courville, Yoshua Bengio
2014	A*	`conf`	Deep Generative Stochastic Networks Trainable by Backprop. ICML Yoshua Bengio, Eric Laufer, Guillaume Alain, Jason Yosinski
2014	J	`jnl`	What regularized auto-encoders learn from the data-generating distribution. J. Mach. Learn. Res. Guillaume Alain, Yoshua Bengio
2013	J	`jnl`	Generalized Denoising Auto-Encoders as Generative Models CoRR Yoshua Bengio, Li Yao, Guillaume Alain, Pascal Vincent
2013	—	`conf`	Generalized Denoising Auto-Encoders as Generative Models. NIPS Yoshua Bengio, Li Yao, Guillaume Alain, Pascal Vincent
2013	A*	`conf`	Regularized Auto-Encoders Estimate Local Statistics ICLR Guillaume Alain, Yoshua Bengio, Salah Rifai
2012	J	`jnl`	Implicit Density Estimation by Local Moment Matching to Sample from Auto-Encoders CoRR Yoshua Bengio, Guillaume Alain, Salah Rifai
2009	J	`jnl`	Model-based clustering of array CGH data. Bioinform. Sohrab P. Shah, K-John Cheung Jr., Nathalie A. Johnson, Guillaume Alain, Randy D. Gascoyne, Douglas E. Horsman, Raymond T. Ng, Kevin P. Murphy