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Comparing Transfer and Meta Learning Approaches on a Unified Few-Shot Classification Benchmark


Apr 06, 2021
Vincent Dumoulin, Neil Houlsby, Utku Evci, Xiaohua Zhai, Ross Goroshin, Sylvain Gelly, Hugo Larochelle


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Interpretable Multi-Modal Hate Speech Detection


Mar 02, 2021
Prashanth Vijayaraghavan, Hugo Larochelle, Deb Roy

* ICML Workshop on AI for Social Good, 2019 
* 5 pages, Accepted at the International Conference on Machine Learning AI for Social Good Workshop, Long Beach, United States, 2019 

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Self-Supervised Equivariant Scene Synthesis from Video


Feb 01, 2021
Cinjon Resnick, Or Litany, Cosmas Heiß, Hugo Larochelle, Joan Bruna, Kyunghyun Cho

* arXiv admin note: text overlap with arXiv:2011.05787 

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An Effective Anti-Aliasing Approach for Residual Networks


Nov 20, 2020
Cristina Vasconcelos, Hugo Larochelle, Vincent Dumoulin, Nicolas Le Roux, Ross Goroshin


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Learned Equivariant Rendering without Transformation Supervision


Nov 11, 2020
Cinjon Resnick, Or Litany, Hugo Larochelle, Joan Bruna, Kyunghyun Cho

* Workshop on Differentiable Vision, Graphics, and Physics in Machine Learning at NeurIPS 2020 

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Learning to Execute Programs with Instruction Pointer Attention Graph Neural Networks


Oct 23, 2020
David Bieber, Charles Sutton, Hugo Larochelle, Daniel Tarlow

* Accepted at NeurIPS 2020 

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Revisiting Fundamentals of Experience Replay


Jul 13, 2020
William Fedus, Prajit Ramachandran, Rishabh Agarwal, Yoshua Bengio, Hugo Larochelle, Mark Rowland, Will Dabney

* Published at ICML 2020. First two authors contributed equally and code available at https://github.com/google-research/google-research/tree/master/experience_replay 

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Learning Graph Structure With A Finite-State Automaton Layer


Jul 09, 2020
Daniel D. Johnson, Hugo Larochelle, Daniel Tarlow

* Submitted to NeurIPS 2020 

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A Universal Representation Transformer Layer for Few-Shot Image Classification


Jun 25, 2020
Lu Liu, William Hamilton, Guodong Long, Jing Jiang, Hugo Larochelle


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Improving Reproducibility in Machine Learning Research (A Report from the NeurIPS 2019 Reproducibility Program)


Apr 02, 2020
Joelle Pineau, Philippe Vincent-Lamarre, Koustuv Sinha, Vincent Larivière, Alina Beygelzimer, Florence d'Alché-Buc, Emily Fox, Hugo Larochelle


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On-the-Fly Adaptation of Source Code Models using Meta-Learning


Mar 26, 2020
Disha Shrivastava, Hugo Larochelle, Daniel Tarlow


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Your GAN is Secretly an Energy-based Model and You Should use Discriminator Driven Latent Sampling


Mar 24, 2020
Tong Che, Ruixiang Zhang, Jascha Sohl-Dickstein, Hugo Larochelle, Liam Paull, Yuan Cao, Yoshua Bengio


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DIBS: Diversity inducing Information Bottleneck in Model Ensembles


Mar 10, 2020
Samarth Sinha, Homanga Bharadhwaj, Anirudh Goyal, Hugo Larochelle, Animesh Garg, Florian Shkurti

* Samarth Sinha* and Homanga Bharadhwaj* contributed equally to this work. Code will be released at https://github.com/rvl-lab-utoronto/dibs 

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Curriculum By Texture


Mar 03, 2020
Samarth Sinha, Animesh Garg, Hugo Larochelle


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On Catastrophic Interference in Atari 2600 Games


Feb 28, 2020
William Fedus, Dibya Ghosh, John D. Martin, Marc G. Bellemare, Yoshua Bengio, Hugo Larochelle

* First two authors contributed equally. Code available to reproduce experiments at https://github.com/google-research/google-research/tree/master/memento 

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Algorithmic Improvements for Deep Reinforcement Learning applied to Interactive Fiction


Nov 28, 2019
Vishal Jain, William Fedus, Hugo Larochelle, Doina Precup, Marc G. Bellemare

* To appear in Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20). Accepted for Oral presentation 

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Small-GAN: Speeding Up GAN Training Using Core-sets


Oct 29, 2019
Samarth Sinha, Han Zhang, Anirudh Goyal, Yoshua Bengio, Hugo Larochelle, Augustus Odena


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Learning Neural Causal Models from Unknown Interventions


Oct 02, 2019
Nan Rosemary Ke, Olexa Bilaniuk, Anirudh Goyal, Stefan Bauer, Hugo Larochelle, Chris Pal, Yoshua Bengio


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InfoBot: Transfer and Exploration via the Information Bottleneck


Apr 04, 2019
Anirudh Goyal, Riashat Islam, Daniel Strouse, Zafarali Ahmed, Matthew Botvinick, Hugo Larochelle, Yoshua Bengio, Sergey Levine

* Accepted at ICLR'19 

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A RAD approach to deep mixture models


Mar 18, 2019
Laurent Dinh, Jascha Sohl-Dickstein, Razvan Pascanu, Hugo Larochelle

* 9 pages of main content, 4 pages of appendices 

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Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples


Mar 07, 2019
Eleni Triantafillou, Tyler Zhu, Vincent Dumoulin, Pascal Lamblin, Kelvin Xu, Ross Goroshin, Carles Gelada, Kevin Swersky, Pierre-Antoine Manzagol, Hugo Larochelle


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Hyperbolic Discounting and Learning over Multiple Horizons


Feb 28, 2019
William Fedus, Carles Gelada, Yoshua Bengio, Marc G. Bellemare, Hugo Larochelle


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Centroid Networks for Few-Shot Clustering and Unsupervised Few-Shot Classification


Feb 22, 2019
Gabriel Huang, Hugo Larochelle, Simon Lacoste-Julien


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The Hanabi Challenge: A New Frontier for AI Research


Feb 01, 2019
Nolan Bard, Jakob N. Foerster, Sarath Chandar, Neil Burch, Marc Lanctot, H. Francis Song, Emilio Parisotto, Vincent Dumoulin, Subhodeep Moitra, Edward Hughes, Iain Dunning, Shibl Mourad, Hugo Larochelle, Marc G. Bellemare, Michael Bowling

* 37 pages, 5 figures, submitted to Artificial Intelligence 

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Blindfold Baselines for Embodied QA


Nov 12, 2018
Ankesh Anand, Eugene Belilovsky, Kyle Kastner, Hugo Larochelle, Aaron Courville

* NIPS 2018 Visually-Grounded Interaction and Language (ViGilL) Workshop 

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