Hugo Larochelle

194 papers A* 42A 8B 1Journal 115Unranked 23

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	BRIDGE: Predicting Human Task Completion Time From Model Performance. CoRR Fengyuan Liu, Jay Gala, Nilaksh, Dzmitry Bahdanau, Siva Reddy, Hugo Larochelle
2026	J	`jnl`	Detoxifying LLMs via Representation Erasure-Based Preference Optimization. CoRR Nazanin Mohammadi Sepahvand, Eleni Triantafillou, Hugo Larochelle, Doina Precup, Daniel M. Roy, Gintare Karolina Dziugaite
2026	J	`jnl`	Towards Sustainable Investment Policies Informed by Opponent Shaping. CoRR Juan Agustin Duque, Razvan Ciuca, Ayoub Echchahed, Hugo Larochelle, Aaron C. Courville
2025	J	`jnl`	Assessing SAM for Tree Crown Instance Segmentation from Drone Imagery. CoRR Mélisande Teng, Arthur Ouaknine, Etienne Laliberté, Yoshua Bengio, David Rolnick, Hugo Larochelle
2025	J	`jnl`	Bringing SAM to new heights: Leveraging elevation data for tree crown segmentation from drone imagery. CoRR Mélisande Teng, Arthur Ouaknine, Etienne Laliberté, Yoshua Bengio, David Rolnick, Hugo Larochelle
2025	J	`jnl`	CISO: Species Distribution Modeling Conditioned on Incomplete Species Observations. CoRR Hager Radi Abdelwahed, Mélisande Teng, Robin Zbinden, Laura Pollock, Hugo Larochelle, Devis Tuia, David Rolnick
2025	J	`jnl`	Capturing Individual Human Preferences with Reward Features. CoRR André Barreto, Vincent Dumoulin, Yiran Mao, Nicolas Perez Nieves, Bobak Shahriari, Yann N. Dauphin, Doina Precup, Hugo Larochelle
2025	A*	`conf`	Don't flatten, tokenize! Unlocking the key to SoftMoE's efficacy in deep RL. ICLR Ghada Sokar, Johan S. Obando-Ceron, Aaron C. Courville, Hugo Larochelle, Pablo Samuel Castro
2025	J	`jnl`	Identifying birdsong syllables without labelled data. CoRR Mélisande Teng, Julien Boussard, David Rolnick, Hugo Larochelle
2025	J	`jnl`	Low Compute Unlearning via Sparse Representations. Trans. Mach. Learn. Res. Vedant Shah, Frederik Träuble, Ashish Malik, Hugo Larochelle, Michael Curtis Mozer, Sanjeev Arora, Yoshua Bengio, Anirudh Goyal
2025	J	`jnl`	ReviewerToo: Should AI Join The Program Committee? A Look At The Future of Peer Review. CoRR Gaurav Sahu, Hugo Larochelle, Laurent Charlin, Christopher Pal
2025	A*	`conf`	Selective Unlearning via Representation Erasure Using Domain Adversarial Training. ICLR Nazanin Mohammadi Sepahvand, Eleni Triantafillou, Hugo Larochelle, Doina Precup, James J. Clark, Daniel M. Roy, Gintare Karolina Dziugaite
2024	J	`jnl`	A density estimation perspective on learning from pairwise human preferences. Trans. Mach. Learn. Res. Vincent Dumoulin, Daniel D. Johnson, Pablo Samuel Castro, Hugo Larochelle, Yann N. Dauphin
2024	—	`conf`	Consolidating Separate Degradations Model via Weights Fusion and Distillation. WACV (Workshops) Dinesh Daultani, Hugo Larochelle
2024	J	`jnl`	Don't flatten, tokenize! Unlocking the key to SoftMoE's efficacy in deep RL. CoRR Ghada Sokar, Johan S. Obando-Ceron, Aaron C. Courville, Hugo Larochelle, Pablo Samuel Castro
2024	A*	`conf`	Many-Shot In-Context Learning. NeurIPS Rishabh Agarwal, Avi Singh, Lei Zhang, Bernd Bohnet, Luis Rosias, Stephanie C. Y. Chan, Biao Zhang, Ankesh Anand, Zaheer Abbas, Azade Nova, John D. Co-Reyes, Eric Chu, Feryal M. P. Behbahani, Aleksandra Faust, Hugo Larochelle
2024	J	`jnl`	Many-Shot In-Context Learning. CoRR Rishabh Agarwal, Avi Singh, Lei M. Zhang, Bernd Bohnet, Stephanie Chan, Ankesh Anand, Zaheer Abbas, Azade Nova, John D. Co-Reyes, Eric Chu, Feryal M. P. Behbahani, Aleksandra Faust, Hugo Larochelle
2024	J	`jnl`	Optimisation of quantitative brain diffusion-relaxation MRI acquisition protocols with physics-informed machine learning. Medical Image Anal. Álvaro Planchuelo-Gómez, Maxime Descoteaux, Hugo Larochelle, Jana Hutter, Derek K. Jones, Chantal M. W. Tax
2023	J	`jnl`	A density estimation perspective on learning from pairwise human preferences. CoRR Vincent Dumoulin, Daniel D. Johnson, Pablo Samuel Castro, Hugo Larochelle, Yann N. Dauphin
2023	J	`jnl`	Bird Distribution Modelling using Remote Sensing and Citizen Science data. CoRR Mélisande Teng, Amna Elmustafa, Benjamin Akera, Hugo Larochelle, David Rolnick
2023	J	`jnl`	Neural Causal Structure Discovery from Interventions. Trans. Mach. Learn. Res. Nan Rosemary Ke, Olexa Bilaniuk, Anirudh Goyal, Stefan Bauer, Hugo Larochelle, Bernhard Schölkopf, Michael Curtis Mozer, Christopher Pal, Yoshua Bengio
2023	A*	`conf`	Repository-Level Prompt Generation for Large Language Models of Code. ICML Disha Shrivastava, Hugo Larochelle, Daniel Tarlow
2023	J	`jnl`	SatBird: Bird Species Distribution Modeling with Remote Sensing and Citizen Science Data. CoRR Mélisande Teng, Amna Elmustafa, Benjamin Akera, Yoshua Bengio, Hager Radi Abdelwahed, Hugo Larochelle, David Rolnick
2023	A*	`conf`	SatBird: a Dataset for Bird Species Distribution Modeling using Remote Sensing and Citizen Science Data. NeurIPS Mélisande Teng, Amna Elmustafa, Benjamin Akera, Yoshua Bengio, Hager Radi Abdelwahed, Hugo Larochelle, David Rolnick
2023	A*	`conf`	Static Prediction of Runtime Errors by Learning to Execute Programs with External Resource Descriptions. ICLR David Bieber, Rishab Goel, Daniel Zheng, Hugo Larochelle, Daniel Tarlow
2023	J	`jnl`	Unlearning via Sparse Representations. CoRR Vedant Shah, Frederik Träuble, Ashish Malik, Hugo Larochelle, Michael Mozer, Sanjeev Arora, Yoshua Bengio, Anirudh Goyal
2022	A*	`conf`	Fortuitous Forgetting in Connectionist Networks. ICLR Hattie Zhou, Ankit Vani, Hugo Larochelle, Aaron C. Courville
2022	J	`jnl`	Fortuitous Forgetting in Connectionist Networks. CoRR Hattie Zhou, Ankit Vani, Hugo Larochelle, Aaron C. Courville
2022	A*	`conf`	Head2Toe: Utilizing Intermediate Representations for Better Transfer Learning. ICML Utku Evci, Vincent Dumoulin, Hugo Larochelle, Michael C. Mozer
2022	J	`jnl`	Head2Toe: Utilizing Intermediate Representations for Better Transfer Learning. CoRR Utku Evci, Vincent Dumoulin, Hugo Larochelle, Michael C. Mozer
2022	A*	`conf`	Matching Feature Sets for Few-Shot Image Classification. CVPR Arman Afrasiyabi, Hugo Larochelle, Jean-François Lalonde, Christian Gagné
2022	J	`jnl`	Matching Feature Sets for Few-Shot Image Classification. CoRR Arman Afrasiyabi, Hugo Larochelle, Jean-François Lalonde, Christian Gagné
2022	J	`jnl`	Repository-Level Prompt Generation for Large Language Models of Code. CoRR Disha Shrivastava, Hugo Larochelle, Daniel Tarlow
2022	J	`jnl`	Static Prediction of Runtime Errors by Learning to Execute Programs with External Resource Descriptions. CoRR David Bieber, Rishab Goel, Daniel Zheng, Hugo Larochelle, Daniel Tarlow
2022	J	`jnl`	Teaching Algorithmic Reasoning via In-context Learning. CoRR Hattie Zhou, Azade Nova, Hugo Larochelle, Aaron C. Courville, Behnam Neyshabur, Hanie Sedghi
2022	—	`conf`	Uniform Priors for Data-Efficient Learning. CVPR Workshops Samarth Sinha, Karsten Roth, Anirudh Goyal, Marzyeh Ghassemi, Zeynep Akata, Hugo Larochelle, Animesh Garg
2021	—	`conf`	A Unified Few-Shot Classification Benchmark to Compare Transfer and Meta Learning Approaches. NeurIPS Datasets and Benchmarks Vincent Dumoulin, Neil Houlsby, Utku Evci, Xiaohua Zhai, Ross Goroshin, Sylvain Gelly, Hugo Larochelle
2021	A*	`conf`	A Universal Representation Transformer Layer for Few-Shot Image Classification. ICLR Lu Liu, William L. Hamilton, Guodong Long, Jing Jiang, Hugo Larochelle
2021	J	`jnl`	Comparing Transfer and Meta Learning Approaches on a Unified Few-Shot Classification Benchmark. CoRR Vincent Dumoulin, Neil Houlsby, Utku Evci, Xiaohua Zhai, Ross Goroshin, Sylvain Gelly, Hugo Larochelle
2021	A*	`conf`	DIBS: Diversity Inducing Information Bottleneck in Model Ensembles. AAAI Samarth Sinha, Homanga Bharadhwaj, Anirudh Goyal, Hugo Larochelle, Animesh Garg, Florian Shkurti
2021	A*	`conf`	Impact of Aliasing on Generalization in Deep Convolutional Networks. ICCV Cristina Nader Vasconcelos, Hugo Larochelle, Vincent Dumoulin, Rob Romijnders, Nicolas Le Roux, Ross Goroshin
2021	J	`jnl`	Impact of Aliasing on Generalization in Deep Convolutional Networks. CoRR Cristina Nader Vasconcelos, Hugo Larochelle, Vincent Dumoulin, Rob Romijnders, Nicolas Le Roux, Ross Goroshin
2021	J	`jnl`	Improving Reproducibility in Machine Learning Research(A Report from the NeurIPS 2019 Reproducibility Program). J. Mach. Learn. Res. Joelle Pineau, Philippe Vincent-Lamarre, Koustuv Sinha, Vincent Larivière, Alina Beygelzimer, Florence d'Alché-Buc, Emily B. Fox, Hugo Larochelle
2021	J	`jnl`	Interpretable Multi-Modal Hate Speech Detection. CoRR Prashanth Vijayaraghavan, Hugo Larochelle, Deb Roy
2021	A*	`conf`	Learning a Universal Template for Few-shot Dataset Generalization. ICML Eleni Triantafillou, Hugo Larochelle, Richard S. Zemel, Vincent Dumoulin
2021	J	`jnl`	Learning a Universal Template for Few-shot Dataset Generalization. CoRR Eleni Triantafillou, Hugo Larochelle, Richard S. Zemel, Vincent Dumoulin
2021	A*	`conf`	Learning to Combine Per-Example Solutions for Neural Program Synthesis. NeurIPS Disha Shrivastava, Hugo Larochelle, Daniel Tarlow
2021	J	`jnl`	Learning to Combine Per-Example Solutions for Neural Program Synthesis. CoRR Disha Shrivastava, Hugo Larochelle, Daniel Tarlow
2021	J	`jnl`	Self-Supervised Equivariant Scene Synthesis from Video. CoRR Cinjon Resnick, Or Litany, Cosmas Heiß, Hugo Larochelle, Joan Bruna, Kyunghyun Cho
2020	J	`jnl`	A Universal Representation Transformer Layer for Few-Shot Image Classification. CoRR Lu Liu, William L. Hamilton, Guodong Long, Jing Jiang, Hugo Larochelle
2020	A*	`ed.`	Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual. NeurIPS Hugo Larochelle, Marc'Aurelio Ranzato, Raia Hadsell, Maria-Florina Balcan, Hsuan-Tien Lin
2020	A*	`conf`	Algorithmic Improvements for Deep Reinforcement Learning Applied to Interactive Fiction. AAAI Vishal Jain, William Fedus, Hugo Larochelle, Doina Precup, Marc G. Bellemare
2020	J	`jnl`	An Effective Anti-Aliasing Approach for Residual Networks. CoRR Cristina Nader Vasconcelos, Hugo Larochelle, Vincent Dumoulin, Nicolas Le Roux, Ross Goroshin
2020	A*	`conf`	Curriculum By Smoothing. NeurIPS Samarth Sinha, Animesh Garg, Hugo Larochelle
2020	J	`jnl`	Curriculum By Texture. CoRR Samarth Sinha, Animesh Garg, Hugo Larochelle
2020	J	`jnl`	DIBS: Diversity inducing Information Bottleneck in Model Ensembles. CoRR Samarth Sinha, Homanga Bharadhwaj, Anirudh Goyal, Hugo Larochelle, Animesh Garg, Florian Shkurti
2020	J	`jnl`	Improving Reproducibility in Machine Learning Research (A Report from the NeurIPS 2019 Reproducibility Program). CoRR Joelle Pineau, Philippe Vincent-Lamarre, Koustuv Sinha, Vincent Larivière, Alina Beygelzimer, Florence d'Alché-Buc, Emily B. Fox, Hugo Larochelle
2020	A*	`conf`	Language GANs Falling Short. ICLR Massimo Caccia, Lucas Caccia, William Fedus, Hugo Larochelle, Joelle Pineau, Laurent Charlin
2020	J	`jnl`	Learned Equivariant Rendering without Transformation Supervision. CoRR Cinjon Resnick, Or Litany, Hugo Larochelle, Joan Bruna, Kyunghyun Cho
2020	A*	`conf`	Learning Graph Structure With A Finite-State Automaton Layer. NeurIPS Daniel D. Johnson, Hugo Larochelle, Daniel Tarlow
2020	J	`jnl`	Learning Graph Structure With A Finite-State Automaton Layer. CoRR Daniel D. Johnson, Hugo Larochelle, Daniel Tarlow
2020	A*	`conf`	Learning to Execute Programs with Instruction Pointer Attention Graph Neural Networks. NeurIPS David Bieber, Charles Sutton, Hugo Larochelle, Daniel Tarlow
2020	J	`jnl`	Learning to Execute Programs with Instruction Pointer Attention Graph Neural Networks. CoRR David Bieber, Charles Sutton, Hugo Larochelle, Daniel Tarlow
2020	A*	`conf`	Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples. ICLR Eleni Triantafillou, Tyler Zhu, Vincent Dumoulin, Pascal Lamblin, Utku Evci, Kelvin Xu, Ross Goroshin, Carles Gelada, Kevin Swersky, Pierre-Antoine Manzagol, Hugo Larochelle
2020	J	`jnl`	On Catastrophic Interference in Atari 2600 Games. CoRR William Fedus, Dibya Ghosh, John D. Martin, Marc G. Bellemare, Yoshua Bengio, Hugo Larochelle
2020	A*	`conf`	Revisiting Fundamentals of Experience Replay. ICML William Fedus, Prajit Ramachandran, Rishabh Agarwal, Yoshua Bengio, Hugo Larochelle, Mark Rowland, Will Dabney
2020	J	`jnl`	Revisiting Fundamentals of Experience Replay. CoRR William Fedus, Prajit Ramachandran, Rishabh Agarwal, Yoshua Bengio, Hugo Larochelle, Mark Rowland, Will Dabney
2020	A*	`conf`	Small-GAN: Speeding up GAN Training using Core-Sets. ICML Samarth Sinha, Han Zhang, Anirudh Goyal, Yoshua Bengio, Hugo Larochelle, Augustus Odena
2020	J	`jnl`	The Hanabi challenge: A new frontier for AI research. Artif. Intell. 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
2020	A*	`conf`	Your GAN is Secretly an Energy-based Model and You Should Use Discriminator Driven Latent Sampling. NeurIPS Tong Che, Ruixiang Zhang, Jascha Sohl-Dickstein, Hugo Larochelle, Liam Paull, Yuan Cao, Yoshua Bengio
2020	J	`jnl`	Your GAN is Secretly an Energy-based Model and You Should use Discriminator Driven Latent Sampling. CoRR Tong Che, Ruixiang Zhang, Jascha Sohl-Dickstein, Hugo Larochelle, Liam Paull, Yuan Cao, Yoshua Bengio
2019	—	`conf`	A RAD approach to deep mixture models. DGS@ICLR Laurent Dinh, Jascha Sohl-Dickstein, Razvan Pascanu, Hugo Larochelle
2019	J	`jnl`	A RAD approach to deep mixture models. CoRR Laurent Dinh, Jascha Sohl-Dickstein, Razvan Pascanu, Hugo Larochelle
2019	A*	`ed.`	Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada. NeurIPS Hanna M. Wallach, Hugo Larochelle, Alina Beygelzimer, Florence d'Alché-Buc, Emily B. Fox, Roman Garnett
2019	J	`jnl`	Algorithmic Improvements for Deep Reinforcement Learning applied to Interactive Fiction. CoRR Vishal Jain, William Fedus, Hugo Larochelle, Doina Precup, Marc G. Bellemare
2019	J	`jnl`	Centroid Networks for Few-Shot Clustering and Unsupervised Few-Shot Classification. CoRR Gabriel Huang, Hugo Larochelle, Simon Lacoste-Julien
2019	J	`jnl`	Hyperbolic Discounting and Learning over Multiple Horizons. CoRR William Fedus, Carles Gelada, Yoshua Bengio, Marc G. Bellemare, Hugo Larochelle
2019	—	`conf`	InfoBot: Transfer and Exploration via the Information Bottleneck. ICLR (Poster) Anirudh Goyal, Riashat Islam, Daniel Strouse, Zafarali Ahmed, Hugo Larochelle, Matthew M. Botvinick, Yoshua Bengio, Sergey Levine
2019	J	`jnl`	InfoBot: Transfer and Exploration via the Information Bottleneck. CoRR Anirudh Goyal, Riashat Islam, Daniel Strouse, Zafarali Ahmed, Matthew M. Botvinick, Hugo Larochelle, Sergey Levine, Yoshua Bengio
2019	J	`jnl`	Learning Neural Causal Models from Unknown Interventions. CoRR Nan Rosemary Ke, Olexa Bilaniuk, Anirudh Goyal, Stefan Bauer, Hugo Larochelle, Chris Pal, Yoshua Bengio
2019	J	`jnl`	Machine behaviour. Nat. Iyad Rahwan, Manuel Cebrián, Nick Obradovich, Josh C. Bongard, Jean-François Bonnefon, Cynthia Breazeal, Jacob W. Crandall, Nicholas A. Christakis, Iain D. Couzin, Matthew O. Jackson, Nicholas R. Jennings, Ece Kamar, Isabel M. Kloumann, Hugo Larochelle, David Lazer, Richard McElreath, Alan Mislove, David C. Parkes, Alex 'Sandy' Pentland, Margaret E. Roberts, Azim Shariff, Joshua B. Tenenbaum, Michael P. Wellman
2019	J	`jnl`	Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples. CoRR Eleni Triantafillou, Tyler Zhu, Vincent Dumoulin, Pascal Lamblin, Kelvin Xu, Ross Goroshin, Carles Gelada, Kevin Swersky, Pierre-Antoine Manzagol, Hugo Larochelle
2019	—	`conf`	Recall Traces: Backtracking Models for Efficient Reinforcement Learning. ICLR (Poster) Anirudh Goyal, Philemon Brakel, William Fedus, Soumye Singhal, Timothy P. Lillicrap, Sergey Levine, Hugo Larochelle, Yoshua Bengio
2019	J	`jnl`	Small-GAN: Speeding Up GAN Training Using Core-sets. CoRR Samarth Sinha, Han Zhang, Anirudh Goyal, Yoshua Bengio, Hugo Larochelle, Augustus Odena
2019	J	`jnl`	The Hanabi Challenge: A New Frontier for AI Research. CoRR 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
2018	A*	`ed.`	Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, NeurIPS 2018, December 3-8, 2018, Montréal, Canada. NeurIPS Samy Bengio, Hanna M. Wallach, Hugo Larochelle, Kristen Grauman, Nicolò Cesa-Bianchi, Roman Garnett
2018	J	`jnl`	Blindfold Baselines for Embodied QA. CoRR Ankesh Anand, Eugene Belilovsky, Kyle Kastner, Hugo Larochelle, Aaron C. Courville
2018	J	`jnl`	Disentangling the independently controllable factors of variation by interacting with the world. CoRR Valentin Thomas, Emmanuel Bengio, William Fedus, Jules Pondard, Philippe Beaudoin, Hugo Larochelle, Joelle Pineau, Doina Precup, Yoshua Bengio
2018	—	`conf`	HoME: a Household Multimodal Environment. ICLR (Workshop) Simon Brodeur, Ethan Perez, Ankesh Anand, Florian Golemo, Luca Celotti, Florian Strub, Jean Rouat, Hugo Larochelle, Aaron C. Courville
2018	J	`jnl`	Language GANs Falling Short. CoRR Massimo Caccia, Lucas Caccia, William Fedus, Hugo Larochelle, Joelle Pineau, Laurent Charlin
2018	—	`conf`	Meta-Learning for Batch Mode Active Learning. ICLR (Workshop) Sachin Ravi, Hugo Larochelle
2018	—	`conf`	Meta-Learning for Semi-Supervised Few-Shot Classification. ICLR (Poster) Mengye Ren, Eleni Triantafillou, Sachin Ravi, Jake Snell, Kevin Swersky, Joshua B. Tenenbaum, Hugo Larochelle, Richard S. Zemel
2018	J	`jnl`	Meta-Learning for Semi-Supervised Few-Shot Classification. CoRR Mengye Ren, Eleni Triantafillou, Sachin Ravi, Jake Snell, Kevin Swersky, Joshua B. Tenenbaum, Hugo Larochelle, Richard S. Zemel
2018	J	`jnl`	Recall Traces: Backtracking Models for Efficient Reinforcement Learning. CoRR Anirudh Goyal, Philemon Brakel, William Fedus, Timothy P. Lillicrap, Sergey Levine, Hugo Larochelle, Yoshua Bengio
2018	J	`jnl`	Traffic Analytics With Low-Frame-Rate Videos. IEEE Trans. Circuits Syst. Video Technol. Zhiming Luo, Pierre-Marc Jodoin, Song-Zhi Su, Shao-Zi Li, Hugo Larochelle
2017	—	`conf`	A Meta-Learning Perspective on Cold-Start Recommendations for Items. NIPS Manasi Vartak, Arvind Thiagarajan, Conrado Miranda, Jeshua Bratman, Hugo Larochelle
2017	J	`jnl`	Brain tumor segmentation with Deep Neural Networks. Medical Image Anal. Mohammad Havaei, Axel Davy, David Warde-Farley, Antoine Biard, Aaron C. Courville, Yoshua Bengio, Chris Pal, Pierre-Marc Jodoin, Hugo Larochelle
2017	J	`jnl`	Document Neural Autoregressive Distribution Estimation. J. Mach. Learn. Res. Stanislas Lauly, Yin Zheng, Alexandre Allauzen, Hugo Larochelle
2017	—	`ch.`	Domain-Adversarial Training of Neural Networks. Domain Adaptation in Computer Vision Applications Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan, Pascal Germain, Hugo Larochelle, François Laviolette, Mario Marchand, Victor S. Lempitsky
2017	A*	`conf`	GuessWhat?! Visual Object Discovery through Multi-modal Dialogue. CVPR Harm de Vries, Florian Strub, Sarath Chandar, Olivier Pietquin, Hugo Larochelle, Aaron C. Courville
2017	J	`jnl`	HoME: a Household Multimodal Environment. CoRR Simon Brodeur, Ethan Perez, Ankesh Anand, Florian Golemo, Luca Celotti, Florian Strub, Jean Rouat, Hugo Larochelle, Aaron C. Courville
2017	—	`conf`	Learn to Track: Deep Learning for Tractography. MICCAI (1) Philippe Poulin, Marc-Alexandre Côté, Jean-Christophe Houde, Laurent Petit, Peter F. Neher, Klaus H. Maier-Hein, Hugo Larochelle, Maxime Descoteaux
2017	—	`conf`	Modulating early visual processing by language. NIPS Harm de Vries, Florian Strub, Jérémie Mary, Hugo Larochelle, Olivier Pietquin, Aaron C. Courville
2017	J	`jnl`	Modulating early visual processing by language. CoRR Harm de Vries, Florian Strub, Jérémie Mary, Hugo Larochelle, Olivier Pietquin, Aaron C. Courville
2017	J	`jnl`	Movie Description. Int. J. Comput. Vis. Anna Rohrbach, Atousa Torabi, Marcus Rohrbach, Niket Tandon, Christopher Joseph Pal, Hugo Larochelle, Aaron C. Courville, Bernt Schiele
2017	J	`jnl`	Multiscale sequence modeling with a learned dictionary. CoRR Bart van Merriënboer, Amartya Sanyal, Hugo Larochelle, Yoshua Bengio
2017	—	`conf`	Optimization as a Model for Few-Shot Learning. ICLR Sachin Ravi, Hugo Larochelle
2017	—	`conf`	Recurrent Mixture Density Network for Spatiotemporal Visual Attention. ICLR (Poster) Loris Bazzani, Hugo Larochelle, Lorenzo Torresani
2016	J	`jnl`	A Deep and Autoregressive Approach for Topic Modeling of Multimodal Data. IEEE Trans. Pattern Anal. Mach. Intell. Yin Zheng, Yu-Jin Zhang, Hugo Larochelle
2016	J	`jnl`	An Infinite Restricted Boltzmann Machine. Neural Comput. Marc-Alexandre Côté, Hugo Larochelle
2016	A*	`conf`	Autoencoding beyond pixels using a learned similarity metric. ICML Anders Boesen Lindbo Larsen, Søren Kaae Sønderby, Hugo Larochelle, Ole Winther
2016	J	`jnl`	Correlational Neural Networks. Neural Comput. Sarath Chandar, Mitesh M. Khapra, Hugo Larochelle, Balaraman Ravindran
2016	—	`ch.`	Deep Learning Trends for Focal Brain Pathology Segmentation in MRI. Machine Learning for Health Informatics Mohammad Havaei, Nicolas Guizard, Hugo Larochelle, Pierre-Marc Jodoin
2016	J	`jnl`	Deep learning trends for focal brain pathology segmentation in MRI. CoRR Mohammad Havaei, Nicolas Guizard, Hugo Larochelle, Pierre-Marc Jodoin
2016	J	`jnl`	Document Neural Autoregressive Distribution Estimation. CoRR Stanislas Lauly, Yin Zheng, Alexandre Allauzen, Hugo Larochelle
2016	J	`jnl`	Domain-Adversarial Training of Neural Networks. J. Mach. Learn. Res. Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan, Pascal Germain, Hugo Larochelle, François Laviolette, Mario Marchand, Victor S. Lempitsky
2016	A*	`conf`	Dynamic Capacity Networks. ICML Amjad Almahairi, Nicolas Ballas, Tim Cooijmans, Yin Zheng, Hugo Larochelle, Aaron C. Courville
2016	J	`jnl`	GuessWhat?! Visual object discovery through multi-modal dialogue. CoRR Harm de Vries, Florian Strub, Sarath Chandar, Olivier Pietquin, Hugo Larochelle, Aaron C. Courville
2016	J	`jnl`	Hierarchical Memory Networks. CoRR Sarath Chandar, Sungjin Ahn, Hugo Larochelle, Pascal Vincent, Gerald Tesauro, Yoshua Bengio
2016	J	`jnl`	Movie Description. CoRR Anna Rohrbach, Atousa Torabi, Marcus Rohrbach, Niket Tandon, Christopher J. Pal, Hugo Larochelle, Aaron C. Courville, Bernt Schiele
2016	J	`jnl`	Neural Autoregressive Distribution Estimation. CoRR Benigno Uria, Marc-Alexandre Côté, Karol Gregor, Iain Murray, Hugo Larochelle
2016	J	`jnl`	Neural Autoregressive Distribution Estimation. J. Mach. Learn. Res. Benigno Uria, Marc-Alexandre Côté, Karol Gregor, Iain Murray, Hugo Larochelle
2016	J	`jnl`	Recurrent Mixture Density Network for Spatiotemporal Visual Attention. CoRR Loris Bazzani, Hugo Larochelle, Lorenzo Torresani
2016	J	`jnl`	Within-brain classification for brain tumor segmentation. Int. J. Comput. Assist. Radiol. Surg. Mohammad Havaei, Hugo Larochelle, Philippe Poulin, Pierre-Marc Jodoin
2016	J	`jnl`	Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations. CoRR David Krueger, Tegan Maharaj, János Kramár, Mohammad Pezeshki, Nicolas Ballas, Nan Rosemary Ke, Anirudh Goyal, Yoshua Bengio, Hugo Larochelle, Aaron C. Courville, Chris Pal
2015	—	`conf`	A Convolutional Neural Network Approach to Brain Tumor Segmentation. Brainles@MICCAI Mohammad Havaei, Francis Dutil, Chris Pal, Hugo Larochelle, Pierre-Marc Jodoin
2015	J	`jnl`	A Neural Autoregressive Approach to Attention-based Recognition. Int. J. Comput. Vis. Yin Zheng, Richard S. Zemel, Yu-Jin Zhang, Hugo Larochelle
2015	J	`jnl`	An Infinite Restricted Boltzmann Machine. CoRR Marc-Alexandre Côté, Hugo Larochelle
2015	J	`jnl`	Brain Tumor Segmentation with Deep Neural Networks. CoRR Mohammad Havaei, Axel Davy, David Warde-Farley, Antoine Biard, Aaron C. Courville, Yoshua Bengio, Chris Pal, Pierre-Marc Jodoin, Hugo Larochelle
2015	J	`jnl`	Correlational Neural Networks. CoRR Sarath Chandar, Mitesh M. Khapra, Hugo Larochelle, Balaraman Ravindran
2015	A*	`conf`	Describing Videos by Exploiting Temporal Structure. ICCV Li Yao, Atousa Torabi, Kyunghyun Cho, Nicolas Ballas, Christopher J. Pal, Hugo Larochelle, Aaron C. Courville
2015	J	`jnl`	Domain-Adversarial Training of Neural Networks. CoRR Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan, Pascal Germain, Hugo Larochelle, François Laviolette, Mario Marchand, Victor S. Lempitsky
2015	J	`jnl`	Dynamic Capacity Networks. CoRR Amjad Almahairi, Nicolas Ballas, Tim Cooijmans, Yin Zheng, Hugo Larochelle, Aaron C. Courville
2015	J	`jnl`	Guest Editorial: Deep Learning for Multimedia Computing. IEEE Trans. Multim. Guo-Jun Qi, Hugo Larochelle, Benoit Huet, Jiebo Luo, Kai Yu
2015	A*	`conf`	MADE: Masked Autoencoder for Distribution Estimation. ICML Mathieu Germain, Karol Gregor, Iain Murray, Hugo Larochelle
2015	J	`jnl`	MADE: Masked Autoencoder for Distribution Estimation. CoRR Mathieu Germain, Karol Gregor, Iain Murray, Hugo Larochelle
2015	—	`ed.`	Proceedings of the 3rd Workshop on Continuous Vector Space Models and their Compositionality, CVSC 2015, Beijing, China, July 26-31, 2015 CVSC Alexandre Allauzen, Edward Grefenstette, Karl Moritz Hermann, Hugo Larochelle, Scott Wen-tau Yih
2015	—	`conf`	Proceedings of the 3rd Workshop on Continuous Vector Space Models and their Compositionality. CVSC Alexandre Allauzen, Edward Grefenstette, Karl Moritz Hermann, Hugo Larochelle, Scott Wen-tau Yih
2015	J	`jnl`	Using Descriptive Video Services to Create a Large Data Source for Video Annotation Research. CoRR Atousa Torabi, Christopher J. Pal, Hugo Larochelle, Aaron C. Courville
2015	A*	`conf`	Using a Recursive Neural Network to Learn an Agent's Decision Model for Plan Recognition. IJCAI Francis Bisson, Hugo Larochelle, Froduald Kabanza
2015	J	`jnl`	Video Description Generation Incorporating Spatio-Temporal Features and a Soft-Attention Mechanism. CoRR Li Yao, Atousa Torabi, Kyunghyun Cho, Nicolas Ballas, Christopher Joseph Pal, Hugo Larochelle, Aaron C. Courville
2015	J	`jnl`	Within-Brain Classification for Brain Tumor Segmentation. CoRR Mohammad Havaei, Hugo Larochelle, Philippe Poulin, Pierre-Marc Jodoin
2014	J	`jnl`	A Deep and Autoregressive Approach for Topic Modeling of Multimodal Data. CoRR Yin Zheng, Yu-Jin Zhang, Hugo Larochelle
2014	A*	`conf`	A Deep and Tractable Density Estimator. ICML Benigno Uria, Iain Murray, Hugo Larochelle
2014	A*	`conf`	Agnostic Bayesian Learning of Ensembles. ICML Alexandre Lacoste, Mario Marchand, François Laviolette, Hugo Larochelle
2014	—	`conf`	An Autoencoder Approach to Learning Bilingual Word Representations. NIPS A. P. Sarath Chandar, Stanislas Lauly, Hugo Larochelle, Mitesh M. Khapra, Balaraman Ravindran, Vikas C. Raykar, Amrita Saha
2014	J	`jnl`	An Autoencoder Approach to Learning Bilingual Word Representations. CoRR A. P. Sarath Chandar, Stanislas Lauly, Hugo Larochelle, Mitesh M. Khapra, Balaraman Ravindran, Vikas C. Raykar, Amrita Saha
2014	J	`jnl`	Domain-Adversarial Neural Networks. CoRR Hana Ajakan, Pascal Germain, Hugo Larochelle, François Laviolette, Mario Marchand
2014	B	`conf`	Efficient Interactive Brain Tumor Segmentation as Within-Brain kNN Classification. ICPR Mohammad Havaei, Pierre-Marc Jodoin, Hugo Larochelle
2014	J	`jnl`	Learning Multilingual Word Representations using a Bag-of-Words Autoencoder. CoRR Stanislas Lauly, Alex Boulanger, Hugo Larochelle
2014	A*	`conf`	Leveraging user libraries to bootstrap collaborative filtering. KDD Laurent Charlin, Richard S. Zemel, Hugo Larochelle
2014	—	`ed.`	Proceedings of the 2nd Workshop on Continuous Vector Space Models and their Compositionality, CVSC@EACL 2014, Gothenburg, Sweden, April 26-30, 2014 CVSC@EACL Alexandre Allauzen, Raffaella Bernardi, Edward Grefenstette, Hugo Larochelle, Christopher D. Manning, Scott Wen-tau Yih
2014	A	`conf`	Sequential Model-Based Ensemble Optimization. UAI Alexandre Lacoste, Hugo Larochelle, Mario Marchand, François Laviolette
2014	J	`jnl`	Sequential Model-Based Ensemble Optimization. CoRR Alexandre Lacoste, Hugo Larochelle, François Laviolette, Mario Marchand
2014	A*	`conf`	Topic Modeling of Multimodal Data: An Autoregressive Approach. CVPR Yin Zheng, Yu-Jin Zhang, Hugo Larochelle
2013	J	`jnl`	A Deep and Tractable Density Estimator. CoRR Benigno Uria, Iain Murray, Hugo Larochelle
2013	J	`jnl`	A Supervised Neural Autoregressive Topic Model for Simultaneous Image Classification and Annotation CoRR Yin Zheng, Yu-Jin Zhang, Hugo Larochelle
2013	J	`jnl`	Guest Editors' Introduction: Special Section on Learning Deep Architectures. IEEE Trans. Pattern Anal. Mach. Intell. Samy Bengio, Li Deng, Hugo Larochelle, Honglak Lee, Ruslan Salakhutdinov
2013	J	`jnl`	NADE: The real-valued neural autoregressive density-estimator. CoRR Benigno Uria, Iain Murray, Hugo Larochelle
2013	—	`ed.`	Proceedings of the Workshop on Continuous Vector Space Models and their Compositionality, CVSM@ACL 2013, Sofia, Bulgaria, August 9, 2013 CVSM@ACL Alexandre Allauzen, Hugo Larochelle, Christopher D. Manning, Richard Socher
2013	—	`conf`	RNADE: The real-valued neural autoregressive density-estimator. NIPS Benigno Uria, Iain Murray, Hugo Larochelle
2012	—	`conf`	A Neural Autoregressive Topic Model. NIPS Hugo Larochelle, Stanislas Lauly
2012	J	`jnl`	Conditional Restricted Boltzmann Machines for Structured Output Prediction CoRR Volodymyr Mnih, Hugo Larochelle, Geoffrey E. Hinton
2012	J	`jnl`	Detonation Classification from acoustic Signature with the Restricted Boltzmann Machine. Comput. Intell. Yoshua Bengio, Nicolas Chapados, Olivier Delalleau, Hugo Larochelle, Xavier Saint-Mleux, Christian Hudon, Jérôme Louradour
2012	J	`jnl`	Learning Algorithms for the Classification Restricted Boltzmann Machine. J. Mach. Learn. Res. Hugo Larochelle, Michael I. Mandel, Razvan Pascanu, Yoshua Bengio
2012	J	`jnl`	Learning Where to Attend with Deep Architectures for Image Tracking. Neural Comput. Misha Denil, Loris Bazzani, Hugo Larochelle, Nando de Freitas
2012	A	`conf`	Learning to rank by aggregating expert preferences. CIKM Maksims Volkovs, Hugo Larochelle, Richard S. Zemel
2012	J	`jnl`	Nonparametric guidance of autoencoder representations using label information. J. Mach. Learn. Res. Jasper Snoek, Ryan P. Adams, Hugo Larochelle
2012	A	`conf`	On Nonparametric Guidance for Learning Autoencoder Representations. AISTATS Jasper Snoek, Ryan Prescott Adams, Hugo Larochelle
2012	J	`jnl`	Practical Bayesian Optimization of Machine Learning Algorithms CoRR Jasper Snoek, Hugo Larochelle, Ryan Prescott Adams
2012	—	`conf`	Practical Bayesian Optimization of Machine Learning Algorithms. NIPS Jasper Snoek, Hugo Larochelle, Ryan P. Adams
2012	J	`jnl`	Training Restricted Boltzmann Machines on Word Observations CoRR George E. Dahl, Ryan Prescott Adams, Hugo Larochelle
2012	A*	`conf`	Training Restricted Boltzmann Machines on Word Observations. ICML George E. Dahl, Ryan Prescott Adams, Hugo Larochelle
2011	J	`jnl`	Autotagging music with conditional restricted Boltzmann machines CoRR Michael I. Mandel, Razvan Pascanu, Hugo Larochelle, Yoshua Bengio
2011	J	`jnl`	Classification of Sets using Restricted Boltzmann Machines CoRR Jérôme Louradour, Hugo Larochelle
2011	A	`conf`	Classification of Sets using Restricted Boltzmann Machines. UAI Jérôme Louradour, Hugo Larochelle
2011	A	`conf`	Conditional Restricted Boltzmann Machines for Structured Output Prediction. UAI Volodymyr Mnih, Hugo Larochelle, Geoffrey E. Hinton
2011	A*	`conf`	Learning attentional policies for tracking and recognition in video with deep networks. ICML Loris Bazzani, Nando de Freitas, Hugo Larochelle, Vittorio Murino, Jo-Anne Ting
2011	J	`jnl`	Learning where to Attend with Deep Architectures for Image Tracking CoRR Misha Denil, Loris Bazzani, Hugo Larochelle, Nando de Freitas
2011	J	`jnl`	Loss-sensitive Training of Probabilistic Conditional Random Fields CoRR Maksims Volkovs, Hugo Larochelle, Richard S. Zemel
2011	A	`conf`	The Neural Autoregressive Distribution Estimator. AISTATS Hugo Larochelle, Iain Murray
2010	A	`conf`	Efficient Learning of Deep Boltzmann Machines. AISTATS Ruslan Salakhutdinov, Hugo Larochelle
2010	—	`conf`	Learning to combine foveal glimpses with a third-order Boltzmann machine. NIPS Hugo Larochelle, Geoffrey E. Hinton
2010	J	`jnl`	Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion. J. Mach. Learn. Res. Pascal Vincent, Hugo Larochelle, Isabelle Lajoie, Yoshua Bengio, Pierre-Antoine Manzagol
2010	J	`jnl`	Tractable Multivariate Binary Density Estimation and the Restricted Boltzmann Forest. Neural Comput. Hugo Larochelle, Yoshua Bengio, Joseph P. Turian
2009	A	`conf`	Deep Learning using Robust Interdependent Codes. AISTATS Hugo Larochelle, Dumitru Erhan, Pascal Vincent
2009	J	`jnl`	Exploring Strategies for Training Deep Neural Networks. J. Mach. Learn. Res. Hugo Larochelle, Yoshua Bengio, Jérôme Louradour, Pascal Lamblin
2008	A*	`conf`	Classification using discriminative restricted Boltzmann machines. ICML Hugo Larochelle, Yoshua Bengio
2008	A*	`conf`	Extracting and composing robust features with denoising autoencoders. ICML Pascal Vincent, Hugo Larochelle, Yoshua Bengio, Pierre-Antoine Manzagol
2008	A*	`conf`	Zero-data Learning of New Tasks. AAAI Hugo Larochelle, Dumitru Erhan, Yoshua Bengio
2007	A*	`conf`	An empirical evaluation of deep architectures on problems with many factors of variation. ICML Hugo Larochelle, Dumitru Erhan, Aaron C. Courville, James Bergstra, Yoshua Bengio
2006	—	`conf`	Greedy Layer-Wise Training of Deep Networks. NIPS Yoshua Bengio, Pascal Lamblin, Dan Popovici, Hugo Larochelle
2006	J	`jnl`	Nonlocal Estimation of Manifold Structure. Neural Comput. Yoshua Bengio, Martin Monperrus, Hugo Larochelle
2005	—	`conf`	Non-Local Manifold Parzen Windows. NIPS Yoshua Bengio, Hugo Larochelle, Pascal Vincent