Hugo Larochelle

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 107

Top Venues

CoRR

ICML

ICLR

NeurIPS

Publications

Álvaro Planchuelo-Gómez, Maxime Descoteaux, Hugo Larochelle, Jana Hutter, Derek K. Jones, Chantal M. W. Tax
Optimisation of quantitative brain diffusion-relaxation MRI acquisition protocols with physics-informed machine learning. Medical Image Anal. 94 (2024)
Vincent Dumoulin, Daniel D. Johnson, Pablo Samuel Castro, Hugo Larochelle, Yann N. Dauphin
A density estimation perspective on learning from pairwise human preferences. Trans. Mach. Learn. Res. 2024 (2024)
Dinesh Daultani, Hugo Larochelle
Consolidating Separate Degradations Model via Weights Fusion and Distillation. WACV (Workshops) (2024)
Rishabh Agarwal, Avi Singh, Lei M. Zhang, Bernd Bohnet, Stephanie C. Y. Chan, Ankesh Anand, Zaheer Abbas, Azade Nova, John D. Co-Reyes, Eric Chu, Feryal M. P. Behbahani, Aleksandra Faust, Hugo Larochelle
Many-Shot In-Context Learning. CoRR (2024)
Mélisande Teng, Amna Elmustafa, Benjamin Akera, Yoshua Bengio, Hager Radi Abdelwahed, Hugo Larochelle, David Rolnick
SatBird: a Dataset for Bird Species Distribution Modeling using Remote Sensing and Citizen Science Data. NeurIPS (2023)
Disha Shrivastava, Hugo Larochelle, Daniel Tarlow
Repository-Level Prompt Generation for Large Language Models of Code. ICML (2023)
Vincent Dumoulin, Daniel D. Johnson, Pablo Samuel Castro, Hugo Larochelle, Yann N. Dauphin
A density estimation perspective on learning from pairwise human preferences. CoRR (2023)
Vedant Shah, Frederik Träuble, Ashish Malik, Hugo Larochelle, Michael Mozer, Sanjeev Arora, Yoshua Bengio, Anirudh Goyal
Unlearning via Sparse Representations. CoRR (2023)
Mélisande Teng, Amna Elmustafa, Benjamin Akera, Hugo Larochelle, David Rolnick
Bird Distribution Modelling using Remote Sensing and Citizen Science data. CoRR (2023)
Nan Rosemary Ke, Olexa Bilaniuk, Anirudh Goyal, Stefan Bauer, Hugo Larochelle, Bernhard Schölkopf, Michael Curtis Mozer, Christopher Pal, Yoshua Bengio
Neural Causal Structure Discovery from Interventions. Trans. Mach. Learn. Res. 2023 (2023)
David Bieber, Rishab Goel, Daniel Zheng, Hugo Larochelle, Daniel Tarlow
Static Prediction of Runtime Errors by Learning to Execute Programs with External Resource Descriptions. ICLR (2023)
Mélisande Teng, Amna Elmustafa, Benjamin Akera, Yoshua Bengio, Hager Radi Abdelwahed, Hugo Larochelle, David Rolnick
SatBird: Bird Species Distribution Modeling with Remote Sensing and Citizen Science Data. CoRR (2023)
Hattie Zhou, Ankit Vani, Hugo Larochelle, Aaron C. Courville
Fortuitous Forgetting in Connectionist Networks. CoRR (2022)
Arman Afrasiyabi, Hugo Larochelle, Jean-François Lalonde, Christian Gagné
Matching Feature Sets for Few-Shot Image Classification. CoRR (2022)
Hattie Zhou, Azade Nova, Hugo Larochelle, Aaron C. Courville, Behnam Neyshabur, Hanie Sedghi
Teaching Algorithmic Reasoning via In-context Learning. CoRR (2022)
Samarth Sinha, Karsten Roth, Anirudh Goyal, Marzyeh Ghassemi, Zeynep Akata, Hugo Larochelle, Animesh Garg
Uniform Priors for Data-Efficient Learning. CVPR Workshops (2022)
Hattie Zhou, Ankit Vani, Hugo Larochelle, Aaron C. Courville
Fortuitous Forgetting in Connectionist Networks. ICLR (2022)
Arman Afrasiyabi, Hugo Larochelle, Jean-François Lalonde, Christian Gagné
Matching Feature Sets for Few-Shot Image Classification. CVPR (2022)
Disha Shrivastava, Hugo Larochelle, Daniel Tarlow
Repository-Level Prompt Generation for Large Language Models of Code. CoRR (2022)
Utku Evci, Vincent Dumoulin, Hugo Larochelle, Michael C. Mozer
Head2Toe: Utilizing Intermediate Representations for Better Transfer Learning. ICML (2022)
David Bieber, Rishab Goel, Daniel Zheng, Hugo Larochelle, Daniel Tarlow
Static Prediction of Runtime Errors by Learning to Execute Programs with External Resource Descriptions. CoRR (2022)
Utku Evci, Vincent Dumoulin, Hugo Larochelle, Michael C. Mozer
Head2Toe: Utilizing Intermediate Representations for Better Transfer Learning. CoRR (2022)
Cristina Vasconcelos, Hugo Larochelle, Vincent Dumoulin, Rob Romijnders, Nicolas Le Roux, Ross Goroshin
Impact of Aliasing on Generalization in Deep Convolutional Networks. ICCV (2021)
Eleni Triantafillou, Hugo Larochelle, Richard S. Zemel, Vincent Dumoulin
Learning a Universal Template for Few-shot Dataset Generalization. CoRR (2021)
Vincent Dumoulin, Neil Houlsby, Utku Evci, Xiaohua Zhai, Ross Goroshin, Sylvain Gelly, Hugo Larochelle
Comparing Transfer and Meta Learning Approaches on a Unified Few-Shot Classification Benchmark. CoRR (2021)
Prashanth Vijayaraghavan, Hugo Larochelle, Deb Roy
Interpretable Multi-Modal Hate Speech Detection. CoRR (2021)
Vincent Dumoulin, Neil Houlsby, Utku Evci, Xiaohua Zhai, Ross Goroshin, Sylvain Gelly, Hugo Larochelle
A Unified Few-Shot Classification Benchmark to Compare Transfer and Meta Learning Approaches. NeurIPS Datasets and Benchmarks (2021)
Samarth Sinha, Homanga Bharadhwaj, Anirudh Goyal, Hugo Larochelle, Animesh Garg, Florian Shkurti
DIBS: Diversity Inducing Information Bottleneck in Model Ensembles. AAAI (2021)
Lu Liu, William L. Hamilton, Guodong Long, Jing Jiang, Hugo Larochelle
A Universal Representation Transformer Layer for Few-Shot Image Classification. ICLR (2021)
Eleni Triantafillou, Hugo Larochelle, Richard S. Zemel, Vincent Dumoulin
Learning a Universal Template for Few-shot Dataset Generalization. ICML (2021)
Cristina Vasconcelos, Hugo Larochelle, Vincent Dumoulin, Rob Romijnders, Nicolas Le Roux, Ross Goroshin
Impact of Aliasing on Generalization in Deep Convolutional Networks. CoRR (2021)
Cinjon Resnick, Or Litany, Cosmas Heiß, Hugo Larochelle, Joan Bruna, Kyunghyun Cho
Self-Supervised Equivariant Scene Synthesis from Video. CoRR (2021)
Disha Shrivastava, Hugo Larochelle, Daniel Tarlow
Learning to Combine Per-Example Solutions for Neural Program Synthesis. CoRR (2021)
Disha Shrivastava, Hugo Larochelle, Daniel Tarlow
Learning to Combine Per-Example Solutions for Neural Program Synthesis. NeurIPS (2021)
Joelle Pineau, Philippe Vincent-Lamarre, Koustuv Sinha, Vincent Larivière, Alina Beygelzimer, Florence d'Alché-Buc, Emily B. Fox, Hugo Larochelle
Improving Reproducibility in Machine Learning Research(A Report from the NeurIPS 2019 Reproducibility Program). J. Mach. Learn. Res. 22 (2021)
Samarth Sinha, Homanga Bharadhwaj, Anirudh Goyal, Hugo Larochelle, Animesh Garg, Florian Shkurti
DIBS: Diversity inducing Information Bottleneck in Model Ensembles. CoRR (2020)
William Fedus, Prajit Ramachandran, Rishabh Agarwal, Yoshua Bengio, Hugo Larochelle, Mark Rowland, Will Dabney
Revisiting Fundamentals of Experience Replay. ICML (2020)
Tong Che, Ruixiang Zhang, Jascha Sohl-Dickstein, Hugo Larochelle, Liam Paull, Yuan Cao, Yoshua Bengio
Your GAN is Secretly an Energy-based Model and You Should use Discriminator Driven Latent Sampling. CoRR (2020)
Cristina Vasconcelos, Hugo Larochelle, Vincent Dumoulin, Nicolas Le Roux, Ross Goroshin
An Effective Anti-Aliasing Approach for Residual Networks. CoRR (2020)
Joelle Pineau, Philippe Vincent-Lamarre, Koustuv Sinha, Vincent Larivière, Alina Beygelzimer, Florence d'Alché-Buc, Emily B. Fox, Hugo Larochelle
Improving Reproducibility in Machine Learning Research (A Report from the NeurIPS 2019 Reproducibility Program). CoRR (2020)
Daniel D. Johnson, Hugo Larochelle, Daniel Tarlow
Learning Graph Structure With A Finite-State Automaton Layer. NeurIPS (2020)
William Fedus, Dibya Ghosh, John D. Martin, Marc G. Bellemare, Yoshua Bengio, Hugo Larochelle
On Catastrophic Interference in Atari 2600 Games. CoRR (2020)
Vishal Jain, William Fedus, Hugo Larochelle, Doina Precup, Marc G. Bellemare
Algorithmic Improvements for Deep Reinforcement Learning Applied to Interactive Fiction. AAAI (2020)
Lu Liu, William L. Hamilton, Guodong Long, Jing Jiang, Hugo Larochelle
A Universal Representation Transformer Layer for Few-Shot Image Classification. CoRR (2020)
Eleni Triantafillou, Tyler Zhu, Vincent Dumoulin, Pascal Lamblin, Utku Evci, Kelvin Xu, Ross Goroshin, Carles Gelada, Kevin Swersky, Pierre-Antoine Manzagol, Hugo Larochelle
Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples. ICLR (2020)
Samarth Sinha, Animesh Garg, Hugo Larochelle
Curriculum By Smoothing. NeurIPS (2020)
Cinjon Resnick, Or Litany, Hugo Larochelle, Joan Bruna, Kyunghyun Cho
Learned Equivariant Rendering without Transformation Supervision. CoRR (2020)
David Bieber, Charles Sutton, Hugo Larochelle, Daniel Tarlow
Learning to Execute Programs with Instruction Pointer Attention Graph Neural Networks. CoRR (2020)
Daniel D. Johnson, Hugo Larochelle, Daniel Tarlow
Learning Graph Structure With A Finite-State Automaton Layer. CoRR (2020)
Samarth Sinha, Animesh Garg, Hugo Larochelle
Curriculum By Texture. CoRR (2020)
Tong Che, Ruixiang Zhang, Jascha Sohl-Dickstein, Hugo Larochelle, Liam Paull, Yuan Cao, Yoshua Bengio
Your GAN is Secretly an Energy-based Model and You Should Use Discriminator Driven Latent Sampling. NeurIPS (2020)
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
The Hanabi challenge: A new frontier for AI research. Artif. Intell. 280 (2020)
Massimo Caccia, Lucas Caccia, William Fedus, Hugo Larochelle, Joelle Pineau, Laurent Charlin
Language GANs Falling Short. ICLR (2020)
David Bieber, Charles Sutton, Hugo Larochelle, Daniel Tarlow
Learning to Execute Programs with Instruction Pointer Attention Graph Neural Networks. NeurIPS (2020)
Disha Shrivastava, Hugo Larochelle, Daniel Tarlow
On-the-Fly Adaptation of Source Code Models using Meta-Learning. CoRR (2020)
William Fedus, Prajit Ramachandran, Rishabh Agarwal, Yoshua Bengio, Hugo Larochelle, Mark Rowland, Will Dabney
Revisiting Fundamentals of Experience Replay. CoRR (2020)
Samarth Sinha, Han Zhang, Anirudh Goyal, Yoshua Bengio, Hugo Larochelle, Augustus Odena
Small-GAN: Speeding up GAN Training using Core-Sets. ICML (2020)
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
The Hanabi Challenge: A New Frontier for AI Research. CoRR (2019)
Vishal Jain, William Fedus, Hugo Larochelle, Doina Precup, Marc G. Bellemare
Algorithmic Improvements for Deep Reinforcement Learning applied to Interactive Fiction. CoRR (2019)
Samarth Sinha, Han Zhang, Anirudh Goyal, Yoshua Bengio, Hugo Larochelle, Augustus Odena
Small-GAN: Speeding Up GAN Training Using Core-sets. CoRR (2019)
William Fedus, Carles Gelada, Yoshua Bengio, Marc G. Bellemare, Hugo Larochelle
Hyperbolic Discounting and Learning over Multiple Horizons. CoRR (2019)
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
Machine behaviour. Nat. 568 (7753) (2019)
Laurent Dinh, Jascha Sohl-Dickstein, Razvan Pascanu, Hugo Larochelle
A RAD approach to deep mixture models. DGS@ICLR (2019)
Gabriel Huang, Hugo Larochelle, Simon Lacoste-Julien
Centroid Networks for Few-Shot Clustering and Unsupervised Few-Shot Classification. CoRR (2019)
Anirudh Goyal, Riashat Islam, Daniel Strouse, Zafarali Ahmed, Hugo Larochelle, Matthew Botvinick, Yoshua Bengio, Sergey Levine
InfoBot: Transfer and Exploration via the Information Bottleneck. ICLR (Poster) (2019)
Laurent Dinh, Jascha Sohl-Dickstein, Razvan Pascanu, Hugo Larochelle
A RAD approach to deep mixture models. CoRR (2019)
Anirudh Goyal, Riashat Islam, Daniel Strouse, Zafarali Ahmed, Matthew Botvinick, Hugo Larochelle, Sergey Levine, Yoshua Bengio
InfoBot: Transfer and Exploration via the Information Bottleneck. CoRR (2019)
Anirudh Goyal, Philemon Brakel, William Fedus, Soumye Singhal, Timothy P. Lillicrap, Sergey Levine, Hugo Larochelle, Yoshua Bengio
Recall Traces: Backtracking Models for Efficient Reinforcement Learning. ICLR (Poster) (2019)
Eleni Triantafillou, Tyler Zhu, Vincent Dumoulin, Pascal Lamblin, Kelvin Xu, Ross Goroshin, Carles Gelada, Kevin Swersky, Pierre-Antoine Manzagol, Hugo Larochelle
Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples. CoRR (2019)
Nan Rosemary Ke, Olexa Bilaniuk, Anirudh Goyal, Stefan Bauer, Hugo Larochelle, Chris Pal, Yoshua Bengio
Learning Neural Causal Models from Unknown Interventions. CoRR (2019)
Mengye Ren, Eleni Triantafillou, Sachin Ravi, Jake Snell, Kevin Swersky, Joshua B. Tenenbaum, Hugo Larochelle, Richard S. Zemel
Meta-Learning for Semi-Supervised Few-Shot Classification. CoRR (2018)
Mengye Ren, Eleni Triantafillou, Sachin Ravi, Jake Snell, Kevin Swersky, Joshua B. Tenenbaum, Hugo Larochelle, Richard S. Zemel
Meta-Learning for Semi-Supervised Few-Shot Classification. ICLR (Poster) (2018)
Massimo Caccia, Lucas Caccia, William Fedus, Hugo Larochelle, Joelle Pineau, Laurent Charlin
Language GANs Falling Short. CoRR (2018)
Valentin Thomas, Emmanuel Bengio, William Fedus, Jules Pondard, Philippe Beaudoin, Hugo Larochelle, Joelle Pineau, Doina Precup, Yoshua Bengio
Disentangling the independently controllable factors of variation by interacting with the world. CoRR (2018)
Sachin Ravi, Hugo Larochelle
Meta-Learning for Batch Mode Active Learning. ICLR (Workshop) (2018)
Ankesh Anand, Eugene Belilovsky, Kyle Kastner, Hugo Larochelle, Aaron C. Courville
Blindfold Baselines for Embodied QA. CoRR (2018)
Anirudh Goyal, Philemon Brakel, William Fedus, Timothy P. Lillicrap, Sergey Levine, Hugo Larochelle, Yoshua Bengio
Recall Traces: Backtracking Models for Efficient Reinforcement Learning. CoRR (2018)
Simon Brodeur, Ethan Perez, Ankesh Anand, Florian Golemo, Luca Celotti, Florian Strub, Jean Rouat, Hugo Larochelle, Aaron C. Courville
HoME: a Household Multimodal Environment. ICLR (Workshop) (2018)
Zhiming Luo, Pierre-Marc Jodoin, Song-Zhi Su, Shao-Zi Li, Hugo Larochelle
Traffic Analytics With Low-Frame-Rate Videos. IEEE Trans. Circuits Syst. Video Technol. 28 (4) (2018)
Harm de Vries, Florian Strub, Jérémie Mary, Hugo Larochelle, Olivier Pietquin, Aaron C. Courville
Modulating early visual processing by language. CoRR (2017)
Simon Brodeur, Ethan Perez, Ankesh Anand, Florian Golemo, Luca Celotti, Florian Strub, Jean Rouat, Hugo Larochelle, Aaron C. Courville
HoME: a Household Multimodal Environment. CoRR (2017)
Sachin Ravi, Hugo Larochelle
Optimization as a Model for Few-Shot Learning. ICLR (2017)
Anna Rohrbach, Atousa Torabi, Marcus Rohrbach, Niket Tandon, Christopher Joseph Pal, Hugo Larochelle, Aaron C. Courville, Bernt Schiele
Movie Description. Int. J. Comput. Vis. 123 (1) (2017)
Bart van Merriënboer, Amartya Sanyal, Hugo Larochelle, Yoshua Bengio
Multiscale sequence modeling with a learned dictionary. CoRR (2017)
Manasi Vartak, Arvind Thiagarajan, Conrado Miranda, Jeshua Bratman, Hugo Larochelle
A Meta-Learning Perspective on Cold-Start Recommendations for Items. NIPS (2017)
Stanislas Lauly, Yin Zheng, Alexandre Allauzen, Hugo Larochelle
Document Neural Autoregressive Distribution Estimation. J. Mach. Learn. Res. 18 (2017)
Loris Bazzani, Hugo Larochelle, Lorenzo Torresani
Recurrent Mixture Density Network for Spatiotemporal Visual Attention. ICLR (Poster) (2017)
Harm de Vries, Florian Strub, Jérémie Mary, Hugo Larochelle, Olivier Pietquin, Aaron C. Courville
Modulating early visual processing by language. NIPS (2017)
Harm de Vries, Florian Strub, Sarath Chandar, Olivier Pietquin, Hugo Larochelle, Aaron C. Courville
GuessWhat?! Visual Object Discovery through Multi-modal Dialogue. CVPR (2017)
Mohammad Havaei, Axel Davy, David Warde-Farley, Antoine Biard, Aaron C. Courville, Yoshua Bengio, Chris Pal, Pierre-Marc Jodoin, Hugo Larochelle
Brain tumor segmentation with Deep Neural Networks. Medical Image Anal. 35 (2017)
Philippe Poulin, Marc-Alexandre Côté, Jean-Christophe Houde, Laurent Petit, Peter F. Neher, Klaus H. Maier-Hein, Hugo Larochelle, Maxime Descoteaux
Learn to Track: Deep Learning for Tractography. MICCAI (1) (2017)
Sarath Chandar, Sungjin Ahn, Hugo Larochelle, Pascal Vincent, Gerald Tesauro, Yoshua Bengio
Hierarchical Memory Networks. CoRR (2016)
Yin Zheng, Yu-Jin Zhang, Hugo Larochelle
A Deep and Autoregressive Approach for Topic Modeling of Multimodal Data. IEEE Trans. Pattern Anal. Mach. Intell. 38 (6) (2016)
Benigno Uria, Marc-Alexandre Côté, Karol Gregor, Iain Murray, Hugo Larochelle
Neural Autoregressive Distribution Estimation. J. Mach. Learn. Res. 17 (2016)
Stanislas Lauly, Yin Zheng, Alexandre Allauzen, Hugo Larochelle
Document Neural Autoregressive Distribution Estimation. CoRR (2016)
David Krueger, Tegan Maharaj, János Kramár, Mohammad Pezeshki, Nicolas Ballas, Nan Rosemary Ke, Anirudh Goyal, Yoshua Bengio, Hugo Larochelle, Aaron C. Courville, Chris Pal
Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations. CoRR (2016)
Anna Rohrbach, Atousa Torabi, Marcus Rohrbach, Niket Tandon, Christopher J. Pal, Hugo Larochelle, Aaron C. Courville, Bernt Schiele
Movie Description. CoRR (2016)
Harm de Vries, Florian Strub, Sarath Chandar, Olivier Pietquin, Hugo Larochelle, Aaron C. Courville
GuessWhat?! Visual object discovery through multi-modal dialogue. CoRR (2016)
Marc-Alexandre Côté, Hugo Larochelle
An Infinite Restricted Boltzmann Machine. Neural Comput. 28 (7) (2016)
Amjad Almahairi, Nicolas Ballas, Tim Cooijmans, Yin Zheng, Hugo Larochelle, Aaron C. Courville
Dynamic Capacity Networks. ICML (2016)

Hugo Larochelle.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Hugo Larochelle