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Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across Layers

Oct 15, 2020
Alex Lamb, Anirudh Goyal, Agnieszka SĹ‚owik, Michael Mozer, Philippe Beaudoin, Yoshua Bengio


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Object Files and Schemata: Factorizing Declarative and Procedural Knowledge in Dynamical Systems

Jun 30, 2020
Anirudh Goyal, Alex Lamb, Phanideep Gampa, Philippe Beaudoin, Sergey Levine, Charles Blundell, Yoshua Bengio, Michael Mozer

* Under Review, NeurIPS 2020 

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Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules

Jun 30, 2020
Sarthak Mittal, Alex Lamb, Anirudh Goyal, Vikram Voleti, Murray Shanahan, Guillaume Lajoie, Michael Mozer, Yoshua Bengio

* ICML 2020 

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Jigsaw-VAE: Towards Balancing Features in Variational Autoencoders

May 12, 2020
Saeid Asgari Taghanaki, Mohammad Havaei, Alex Lamb, Aditya Sanghi, Ara Danielyan, Tonya Custis


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KaoKore: A Pre-modern Japanese Art Facial Expression Dataset

Feb 20, 2020
Yingtao Tian, Chikahiko Suzuki, Tarin Clanuwat, Mikel Bober-Irizar, Alex Lamb, Asanobu Kitamoto


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SketchTransfer: A Challenging New Task for Exploring Detail-Invariance and the Abstractions Learned by Deep Networks

Dec 25, 2019
Alex Lamb, Sherjil Ozair, Vikas Verma, David Ha

* Accepted WACV 2020 

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KuroNet: Pre-Modern Japanese Kuzushiji Character Recognition with Deep Learning

Oct 21, 2019
Tarin Clanuwat, Alex Lamb, Asanobu Kitamoto

* International Conference on Document Recognition (ICDAR) 2019 [oral] 

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Recurrent Independent Mechanisms

Sep 26, 2019
Anirudh Goyal, Alex Lamb, Jordan Hoffmann, Shagun Sodhani, Sergey Levine, Yoshua Bengio, Bernhard Schölkopf


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GraphMix: Regularized Training of Graph Neural Networks for Semi-Supervised Learning

Sep 25, 2019
Vikas Verma, Meng Qu, Alex Lamb, Yoshua Bengio, Juho Kannala, Jian Tang


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Interpolated Adversarial Training: Achieving Robust Neural Networks without Sacrificing Too Much Accuracy

Jun 29, 2019
Alex Lamb, Vikas Verma, Juho Kannala, Yoshua Bengio


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Interpolated Adversarial Training: Achieving Robust Neural Networks without Sacrificing Accuracy

Jun 16, 2019
Alex Lamb, Vikas Verma, Juho Kannala, Yoshua Bengio


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State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations

May 26, 2019
Alex Lamb, Jonathan Binas, Anirudh Goyal, Sandeep Subramanian, Ioannis Mitliagkas, Denis Kazakov, Yoshua Bengio, Michael C. Mozer

* ICML 2019 [full oral]. arXiv admin note: text overlap with arXiv:1805.08394 

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Adversarial Mixup Resynthesizers

Apr 04, 2019
Christopher Beckham, Sina Honari, Alex Lamb, Vikas Verma, Farnoosh Ghadiri, R Devon Hjelm, Christopher Pal


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Interpolation Consistency Training for Semi-Supervised Learning

Mar 09, 2019
Vikas Verma, Alex Lamb, Juho Kannala, Yoshua Bengio, David Lopez-Paz

* Semi-supervised Learning, Deep Learning, Neural Networks 

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Deep Learning for Classical Japanese Literature

Dec 03, 2018
Tarin Clanuwat, Mikel Bober-Irizar, Asanobu Kitamoto, Alex Lamb, Kazuaki Yamamoto, David Ha

* To appear at Neural Information Processing Systems 2018 Workshop on Machine Learning for Creativity and Design 

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Manifold Mixup: Learning Better Representations by Interpolating Hidden States

Oct 04, 2018
Vikas Verma, Alex Lamb, Christopher Beckham, Amir Najafi, Aaron Courville, Ioannis Mitliagkas, Yoshua Bengio

* ICLR2019 Under Review 

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Fortified Networks: Improving the Robustness of Deep Networks by Modeling the Manifold of Hidden Representations

Apr 07, 2018
Alex Lamb, Jonathan Binas, Anirudh Goyal, Dmitriy Serdyuk, Sandeep Subramanian, Ioannis Mitliagkas, Yoshua Bengio

* Under Review ICML 2018 

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GibbsNet: Iterative Adversarial Inference for Deep Graphical Models

Dec 12, 2017
Alex Lamb, Devon Hjelm, Yaroslav Ganin, Joseph Paul Cohen, Aaron Courville, Yoshua Bengio

* NIPS 2017 

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ACtuAL: Actor-Critic Under Adversarial Learning

Nov 13, 2017
Anirudh Goyal, Nan Rosemary Ke, Alex Lamb, R Devon Hjelm, Chris Pal, Joelle Pineau, Yoshua Bengio


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Adversarially Learned Inference

Feb 21, 2017
Vincent Dumoulin, Ishmael Belghazi, Ben Poole, Olivier Mastropietro, Alex Lamb, Martin Arjovsky, Aaron Courville


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Professor Forcing: A New Algorithm for Training Recurrent Networks

Oct 27, 2016
Alex Lamb, Anirudh Goyal, Ying Zhang, Saizheng Zhang, Aaron Courville, Yoshua Bengio

* NIPS 2016 Accepted Paper 

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Theano: A Python framework for fast computation of mathematical expressions

May 09, 2016
The Theano Development Team, Rami Al-Rfou, Guillaume Alain, Amjad Almahairi, Christof Angermueller, 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 Christiano, Tim Cooijmans, Marc-Alexandre Côté, Myriam Côté, Aaron Courville, Yann N. Dauphin, Olivier Delalleau, Julien Demouth, Guillaume Desjardins, Sander Dieleman, Laurent Dinh, Mélanie Ducoffe, Vincent Dumoulin, Samira Ebrahimi Kahou, Dumitru Erhan, Ziye Fan, Orhan Firat, Mathieu Germain, Xavier Glorot, Ian Goodfellow, Matt Graham, Caglar Gulcehre, 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 Lefrancois, Simon Lemieux, Nicholas Léonard, Zhouhan Lin, Jesse A. Livezey, Cory Lorenz, Jeremiah Lowin, Qianli Ma, Pierre-Antoine Manzagol, Olivier Mastropietro, Robert T. McGibbon, Roland Memisevic, Bart van Merriënboer, Vincent Michalski, Mehdi Mirza, Alberto Orlandi, Christopher 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 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

* 19 pages, 5 figures 

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Variance Reduction in SGD by Distributed Importance Sampling

Apr 16, 2016
Guillaume Alain, Alex Lamb, Chinnadhurai Sankar, Aaron Courville, Yoshua Bengio


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Discriminative Regularization for Generative Models

Feb 15, 2016
Alex Lamb, Vincent Dumoulin, Aaron Courville


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