Hugo Larochelle

According to our database, Hugo Larochelle authored at least 129 papers between 2005 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

A density estimation perspective on learning from pairwise human preferences.

Vincent Dumoulin, Daniel D. Johnson, Pablo Samuel Castro, Hugo Larochelle, Yann N. Dauphin

Trans. Mach. Learn. Res., 2024

Optimisation of quantitative brain diffusion-relaxation MRI acquisition protocols with physics-informed machine learning.

Álvaro Planchuelo-Gómez, Maxime Descoteaux, Hugo Larochelle, Jana Hutter, Derek K. Jones, Chantal M. W. Tax

Medical Image Anal., 2024

Don't flatten, tokenize! Unlocking the key to SoftMoE's efficacy in deep RL.

Ghada Sokar, Johan S. Obando-Ceron, Aaron C. Courville, Hugo Larochelle, Pablo Samuel Castro

CoRR, 2024

Many-Shot In-Context Learning.

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

CoRR, 2024

Consolidating Separate Degradations Model via Weights Fusion and Distillation.

Dinesh Daultani, Hugo Larochelle

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, 2024

2023

Neural Causal Structure Discovery from Interventions.

Nan Rosemary Ke, Olexa Bilaniuk, Anirudh Goyal, Stefan Bauer, Hugo Larochelle, Bernhard Schölkopf, Michael Curtis Mozer, Christopher Pal, Yoshua Bengio

Trans. Mach. Learn. Res., 2023

Unlearning via Sparse Representations.

Vedant Shah, Frederik Träuble, Ashish Malik, Hugo Larochelle, Michael Mozer, Sanjeev Arora, Yoshua Bengio, Anirudh Goyal

CoRR, 2023

SatBird: Bird Species Distribution Modeling with Remote Sensing and Citizen Science Data.

Mélisande Teng, Amna Elmustafa, Benjamin Akera, Yoshua Bengio, Hager Radi Abdelwahed, Hugo Larochelle, David Rolnick

CoRR, 2023

Bird Distribution Modelling using Remote Sensing and Citizen Science data.

Mélisande Teng, Amna Elmustafa, Benjamin Akera, Hugo Larochelle, David Rolnick

CoRR, 2023

SatBird: a Dataset for Bird Species Distribution Modeling using Remote Sensing and Citizen Science Data.

Mélisande Teng, Amna Elmustafa, Benjamin Akera, Yoshua Bengio, Hager Radi Abdelwahed, Hugo Larochelle, David Rolnick

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Repository-Level Prompt Generation for Large Language Models of Code.

Disha Shrivastava, Hugo Larochelle, Daniel Tarlow

Proceedings of the International Conference on Machine Learning, 2023

Static Prediction of Runtime Errors by Learning to Execute Programs with External Resource Descriptions.

David Bieber, Rishab Goel, Daniel Zheng, Hugo Larochelle, Daniel Tarlow

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Teaching Algorithmic Reasoning via In-context Learning.

Hattie Zhou, Azade Nova, Hugo Larochelle, Aaron C. Courville, Behnam Neyshabur, Hanie Sedghi

CoRR, 2022

Head2Toe: Utilizing Intermediate Representations for Better Transfer Learning.

Utku Evci, Vincent Dumoulin, Hugo Larochelle, Michael C. Mozer

Proceedings of the International Conference on Machine Learning, 2022

Fortuitous Forgetting in Connectionist Networks.

Hattie Zhou, Ankit Vani, Hugo Larochelle, Aaron C. Courville

Proceedings of the Tenth International Conference on Learning Representations, 2022

Uniform Priors for Data-Efficient Learning.

Samarth Sinha, Karsten Roth, Anirudh Goyal, Marzyeh Ghassemi, Zeynep Akata, Hugo Larochelle, Animesh Garg

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

Matching Feature Sets for Few-Shot Image Classification.

Arman Afrasiyabi, Hugo Larochelle, Jean-François Lalonde, Christian Gagné

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

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

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

J. Mach. Learn. Res., 2021

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

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

CoRR, 2021

Interpretable Multi-Modal Hate Speech Detection.

Prashanth Vijayaraghavan, Hugo Larochelle, Deb Roy

CoRR, 2021

Self-Supervised Equivariant Scene Synthesis from Video.

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

CoRR, 2021

Learning to Combine Per-Example Solutions for Neural Program Synthesis.

Disha Shrivastava, Hugo Larochelle, Daniel Tarlow

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A Unified Few-Shot Classification Benchmark to Compare Transfer and Meta Learning Approaches.

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

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Learning a Universal Template for Few-shot Dataset Generalization.

Eleni Triantafillou, Hugo Larochelle, Richard S. Zemel, Vincent Dumoulin

Proceedings of the 38th International Conference on Machine Learning, 2021

A Universal Representation Transformer Layer for Few-Shot Image Classification.

Lu Liu, William L. Hamilton, Guodong Long, Jing Jiang, Hugo Larochelle

Proceedings of the 9th International Conference on Learning Representations, 2021

Impact of Aliasing on Generalization in Deep Convolutional Networks.

Cristina Nader Vasconcelos, Hugo Larochelle, Vincent Dumoulin, Rob Romijnders, Nicolas Le Roux, Ross Goroshin

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

DIBS: Diversity Inducing Information Bottleneck in Model Ensembles.

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

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

An Effective Anti-Aliasing Approach for Residual Networks.

Cristina Nader Vasconcelos, Hugo Larochelle, Vincent Dumoulin, Nicolas Le Roux, Ross Goroshin

CoRR, 2020

Learned Equivariant Rendering without Transformation Supervision.

Cinjon Resnick, Or Litany, Hugo Larochelle, Joan Bruna, Kyunghyun Cho

CoRR, 2020

Curriculum By Texture.

Samarth Sinha, Animesh Garg, Hugo Larochelle

CoRR, 2020

On Catastrophic Interference in Atari 2600 Games.

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

CoRR, 2020

The Hanabi challenge: A new frontier for AI research.

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

Artif. Intell., 2020

Curriculum By Smoothing.

Samarth Sinha, Animesh Garg, Hugo Larochelle

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

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

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

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning to Execute Programs with Instruction Pointer Attention Graph Neural Networks.

David Bieber, Charles Sutton, Hugo Larochelle, Daniel Tarlow

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning Graph Structure With A Finite-State Automaton Layer.

Daniel D. Johnson, Hugo Larochelle, Daniel Tarlow

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Small-GAN: Speeding up GAN Training using Core-Sets.

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

Proceedings of the 37th International Conference on Machine Learning, 2020

Revisiting Fundamentals of Experience Replay.

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

Proceedings of the 37th International Conference on Machine Learning, 2020

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

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

Proceedings of the 8th International Conference on Learning Representations, 2020

Language GANs Falling Short.

Massimo Caccia, Lucas Caccia, William Fedus, Hugo Larochelle, Joelle Pineau, Laurent Charlin

Proceedings of the 8th International Conference on Learning Representations, 2020

Algorithmic Improvements for Deep Reinforcement Learning Applied to Interactive Fiction.

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

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Machine behaviour.

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

Nat., 2019

Learning Neural Causal Models from Unknown Interventions.

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

CoRR, 2019

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

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

CoRR, 2019

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

Gabriel Huang, Hugo Larochelle, Simon Lacoste-Julien

CoRR, 2019

Hyperbolic Discounting and Learning over Multiple Horizons.

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

CoRR, 2019

InfoBot: Transfer and Exploration via the Information Bottleneck.

Anirudh Goyal, Riashat Islam, Daniel Strouse, Zafarali Ahmed, Hugo Larochelle, Matthew M. Botvinick, Yoshua Bengio, Sergey Levine

Proceedings of the 7th International Conference on Learning Representations, 2019

Recall Traces: Backtracking Models for Efficient Reinforcement Learning.

Anirudh Goyal, Philemon Brakel, William Fedus, Soumye Singhal, Timothy P. Lillicrap, Sergey Levine, Hugo Larochelle, Yoshua Bengio

Proceedings of the 7th International Conference on Learning Representations, 2019

A RAD approach to deep mixture models.

Laurent Dinh, Jascha Sohl-Dickstein, Razvan Pascanu, Hugo Larochelle

Proceedings of the Deep Generative Models for Highly Structured Data, 2019

2018

Traffic Analytics With Low-Frame-Rate Videos.

Zhiming Luo, Pierre-Marc Jodoin, Song-Zhi Su, Shao-Zi Li, Hugo Larochelle

IEEE Trans. Circuits Syst. Video Technol., 2018

Blindfold Baselines for Embodied QA.

Ankesh Anand, Eugene Belilovsky, Kyle Kastner, Hugo Larochelle, Aaron C. Courville

CoRR, 2018

Recall Traces: Backtracking Models for Efficient Reinforcement Learning.

Anirudh Goyal, Philemon Brakel, William Fedus, Timothy P. Lillicrap, Sergey Levine, Hugo Larochelle, Yoshua Bengio

CoRR, 2018

Disentangling the independently controllable factors of variation by interacting with the world.

Valentin Thomas, Emmanuel Bengio, William Fedus, Jules Pondard, Philippe Beaudoin, Hugo Larochelle, Joelle Pineau, Doina Precup, Yoshua Bengio

CoRR, 2018

Meta-Learning for Semi-Supervised Few-Shot Classification.

Mengye Ren, Eleni Triantafillou, Sachin Ravi, Jake Snell, Kevin Swersky, Joshua B. Tenenbaum, Hugo Larochelle, Richard S. Zemel

Proceedings of the 6th International Conference on Learning Representations, 2018

Meta-Learning for Batch Mode Active Learning.

Sachin Ravi, Hugo Larochelle

Proceedings of the 6th International Conference on Learning Representations, 2018

HoME: a Household Multimodal Environment.

Simon Brodeur, Ethan Perez, Ankesh Anand, Florian Golemo, Luca Celotti, Florian Strub, Jean Rouat, Hugo Larochelle, Aaron C. Courville

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Domain-Adversarial Training of Neural Networks.

Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan, Pascal Germain, Hugo Larochelle, François Laviolette, Mario Marchand, Victor S. Lempitsky

Proceedings of the Domain Adaptation in Computer Vision Applications., 2017

Brain tumor segmentation with Deep Neural Networks.

Mohammad Havaei, Axel Davy, David Warde-Farley, Antoine Biard, Aaron C. Courville, Yoshua Bengio, Chris Pal, Pierre-Marc Jodoin, Hugo Larochelle

Medical Image Anal., 2017

Document Neural Autoregressive Distribution Estimation.

Stanislas Lauly, Yin Zheng, Alexandre Allauzen, Hugo Larochelle

J. Mach. Learn. Res., 2017

Movie Description.

Anna Rohrbach, Atousa Torabi, Marcus Rohrbach, Niket Tandon, Christopher Joseph Pal, Hugo Larochelle, Aaron C. Courville, Bernt Schiele

Int. J. Comput. Vis., 2017

Multiscale sequence modeling with a learned dictionary.

Bart van Merriënboer, Amartya Sanyal, Hugo Larochelle, Yoshua Bengio

CoRR, 2017

Modulating early visual processing by language.

Harm de Vries, Florian Strub, Jérémie Mary, Hugo Larochelle, Olivier Pietquin, Aaron C. Courville

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

A Meta-Learning Perspective on Cold-Start Recommendations for Items.

Manasi Vartak, Arvind Thiagarajan, Conrado Miranda, Jeshua Bratman, Hugo Larochelle

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Learn to Track: Deep Learning for Tractography.

Philippe Poulin, Marc-Alexandre Côté, Jean-Christophe Houde, Laurent Petit, Peter F. Neher, Klaus H. Maier-Hein, Hugo Larochelle, Maxime Descoteaux

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017

Optimization as a Model for Few-Shot Learning.

Sachin Ravi, Hugo Larochelle

Proceedings of the 5th International Conference on Learning Representations, 2017

Recurrent Mixture Density Network for Spatiotemporal Visual Attention.

Loris Bazzani, Hugo Larochelle, Lorenzo Torresani

Proceedings of the 5th International Conference on Learning Representations, 2017

GuessWhat?! Visual Object Discovery through Multi-modal Dialogue.

Harm de Vries, Florian Strub, Sarath Chandar, Olivier Pietquin, Hugo Larochelle, Aaron C. Courville

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

Deep Learning Trends for Focal Brain Pathology Segmentation in MRI.

Mohammad Havaei, Nicolas Guizard, Hugo Larochelle, Pierre-Marc Jodoin

Proceedings of the Machine Learning for Health Informatics, 2016

A Deep and Autoregressive Approach for Topic Modeling of Multimodal Data.

Yin Zheng, Yu-Jin Zhang, Hugo Larochelle

IEEE Trans. Pattern Anal. Mach. Intell., 2016

An Infinite Restricted Boltzmann Machine.

Marc-Alexandre Côté, Hugo Larochelle

Neural Comput., 2016

Correlational Neural Networks.

Sarath Chandar, Mitesh M. Khapra, Hugo Larochelle, Balaraman Ravindran

Neural Comput., 2016

Neural Autoregressive Distribution Estimation.

Benigno Uria, Marc-Alexandre Côté, Karol Gregor, Iain Murray, Hugo Larochelle

J. Mach. Learn. Res., 2016

Domain-Adversarial Training of Neural Networks.

Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan, Pascal Germain, Hugo Larochelle, François Laviolette, Mario Marchand, Victor S. Lempitsky

J. Mach. Learn. Res., 2016

Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations.

David Krueger, Tegan Maharaj, János Kramár, Mohammad Pezeshki, Nicolas Ballas, Nan Rosemary Ke, Anirudh Goyal, Yoshua Bengio, Hugo Larochelle, Aaron C. Courville, Chris Pal

CoRR, 2016

Deep learning trends for focal brain pathology segmentation in MRI.

Mohammad Havaei, Nicolas Guizard, Hugo Larochelle, Pierre-Marc Jodoin

CoRR, 2016

Hierarchical Memory Networks.

Sarath Chandar, Sungjin Ahn, Hugo Larochelle, Pascal Vincent, Gerald Tesauro, Yoshua Bengio

CoRR, 2016

Within-brain classification for brain tumor segmentation.

Mohammad Havaei, Hugo Larochelle, Philippe Poulin, Pierre-Marc Jodoin

Int. J. Comput. Assist. Radiol. Surg., 2016

Autoencoding beyond pixels using a learned similarity metric.

Anders Boesen Lindbo Larsen, Søren Kaae Sønderby, Hugo Larochelle, Ole Winther

Proceedings of the 33nd International Conference on Machine Learning, 2016

Dynamic Capacity Networks.

Amjad Almahairi, Nicolas Ballas, Tim Cooijmans, Yin Zheng, Hugo Larochelle, Aaron C. Courville

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

Guest Editorial: Deep Learning for Multimedia Computing.

Guo-Jun Qi, Hugo Larochelle, Benoit Huet, Jiebo Luo, Kai Yu

IEEE Trans. Multim., 2015

A Neural Autoregressive Approach to Attention-based Recognition.

Yin Zheng, Richard S. Zemel, Yu-Jin Zhang, Hugo Larochelle

Int. J. Comput. Vis., 2015

Video Description Generation Incorporating Spatio-Temporal Features and a Soft-Attention Mechanism.

Li Yao, Atousa Torabi, Kyunghyun Cho, Nicolas Ballas, Christopher Joseph Pal, Hugo Larochelle, Aaron C. Courville

CoRR, 2015

Using Descriptive Video Services to Create a Large Data Source for Video Annotation Research.

Atousa Torabi, Christopher J. Pal, Hugo Larochelle, Aaron C. Courville

CoRR, 2015

A Convolutional Neural Network Approach to Brain Tumor Segmentation.

Mohammad Havaei, Francis Dutil, Chris Pal, Hugo Larochelle, Pierre-Marc Jodoin

Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2015

Using a Recursive Neural Network to Learn an Agent's Decision Model for Plan Recognition.

Francis Bisson, Hugo Larochelle, Froduald Kabanza

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

MADE: Masked Autoencoder for Distribution Estimation.

Mathieu Germain, Karol Gregor, Iain Murray, Hugo Larochelle

Proceedings of the 32nd International Conference on Machine Learning, 2015

Describing Videos by Exploiting Temporal Structure.

Li Yao, Atousa Torabi, Kyunghyun Cho, Nicolas Ballas, Christopher J. Pal, Hugo Larochelle, Aaron C. Courville

Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

Proceedings of the 3rd Workshop on Continuous Vector Space Models and their Compositionality.

Alexandre Allauzen, Edward Grefenstette, Karl Moritz Hermann, Hugo Larochelle, Scott Wen-tau Yih

Proceedings of the 3rd Workshop on Continuous Vector Space Models and their Compositionality, 2015

2014

Learning Multilingual Word Representations using a Bag-of-Words Autoencoder.

Stanislas Lauly, Alex Boulanger, Hugo Larochelle

CoRR, 2014

Domain-Adversarial Neural Networks.

Hana Ajakan, Pascal Germain, Hugo Larochelle, François Laviolette, Mario Marchand

CoRR, 2014

Sequential Model-Based Ensemble Optimization.

Alexandre Lacoste, Hugo Larochelle, Mario Marchand, François Laviolette

Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

An Autoencoder Approach to Learning Bilingual Word Representations.

A. P. Sarath Chandar, Stanislas Lauly, Hugo Larochelle, Mitesh M. Khapra, Balaraman Ravindran, Vikas C. Raykar, Amrita Saha

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Leveraging user libraries to bootstrap collaborative filtering.

Laurent Charlin, Richard S. Zemel, Hugo Larochelle

Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

Efficient Interactive Brain Tumor Segmentation as Within-Brain kNN Classification.

Mohammad Havaei, Pierre-Marc Jodoin, Hugo Larochelle

Proceedings of the 22nd International Conference on Pattern Recognition, 2014

A Deep and Tractable Density Estimator.

Benigno Uria, Iain Murray, Hugo Larochelle

Proceedings of the 31th International Conference on Machine Learning, 2014

Agnostic Bayesian Learning of Ensembles.

Alexandre Lacoste, Mario Marchand, François Laviolette, Hugo Larochelle

Proceedings of the 31th International Conference on Machine Learning, 2014

Topic Modeling of Multimodal Data: An Autoregressive Approach.

Yin Zheng, Yu-Jin Zhang, Hugo Larochelle

Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

2013

Guest Editors' Introduction: Special Section on Learning Deep Architectures.

Samy Bengio, Li Deng, Hugo Larochelle, Honglak Lee, Ruslan Salakhutdinov

IEEE Trans. Pattern Anal. Mach. Intell., 2013

A Supervised Neural Autoregressive Topic Model for Simultaneous Image Classification and Annotation

Yin Zheng, Yu-Jin Zhang, Hugo Larochelle

CoRR, 2013

NADE: The real-valued neural autoregressive density-estimator.

Benigno Uria, Iain Murray, Hugo Larochelle

CoRR, 2013

RNADE: The real-valued neural autoregressive density-estimator.

Benigno Uria, Iain Murray, Hugo Larochelle

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

2012

Learning Where to Attend with Deep Architectures for Image Tracking.

Misha Denil, Loris Bazzani, Hugo Larochelle, Nando de Freitas

Neural Comput., 2012

Nonparametric guidance of autoencoder representations using label information.

Jasper Snoek, Ryan P. Adams, Hugo Larochelle

J. Mach. Learn. Res., 2012

On Nonparametric Guidance for Learning Autoencoder Representations.

Jasper Snoek, Ryan Prescott Adams, Hugo Larochelle

Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Learning Algorithms for the Classification Restricted Boltzmann Machine.

Hugo Larochelle, Michael I. Mandel, Razvan Pascanu, Yoshua Bengio

J. Mach. Learn. Res., 2012

Detonation Classification from acoustic Signature with the Restricted Boltzmann Machine.

Yoshua Bengio, Nicolas Chapados, Olivier Delalleau, Hugo Larochelle, Xavier Saint-Mleux, Christian Hudon, Jérôme Louradour

Comput. Intell., 2012

Practical Bayesian Optimization of Machine Learning Algorithms.

Jasper Snoek, Hugo Larochelle, Ryan P. Adams

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

A Neural Autoregressive Topic Model.

Hugo Larochelle, Stanislas Lauly

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Training Restricted Boltzmann Machines on Word Observations.

George E. Dahl, Ryan Prescott Adams, Hugo Larochelle

Proceedings of the 29th International Conference on Machine Learning, 2012

Learning to rank by aggregating expert preferences.

Maksims Volkovs, Hugo Larochelle, Richard S. Zemel

Proceedings of the 21st ACM International Conference on Information and Knowledge Management, 2012

2011

The Neural Autoregressive Distribution Estimator.

Hugo Larochelle, Iain Murray

Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Loss-sensitive Training of Probabilistic Conditional Random Fields

Maksims Volkovs, Hugo Larochelle, Richard S. Zemel

CoRR, 2011

Autotagging music with conditional restricted Boltzmann machines

Michael I. Mandel, Razvan Pascanu, Hugo Larochelle, Yoshua Bengio

CoRR, 2011

Conditional Restricted Boltzmann Machines for Structured Output Prediction.

Volodymyr Mnih, Hugo Larochelle, Geoffrey E. Hinton

Proceedings of the UAI 2011, 2011

Classification of Sets using Restricted Boltzmann Machines.

Jérôme Louradour, Hugo Larochelle

Proceedings of the UAI 2011, 2011

Learning attentional policies for tracking and recognition in video with deep networks.

Loris Bazzani, Nando de Freitas, Hugo Larochelle, Vittorio Murino, Jo-Anne Ting

Proceedings of the 28th International Conference on Machine Learning, 2011

2010

Tractable Multivariate Binary Density Estimation and the Restricted Boltzmann Forest.

Hugo Larochelle, Yoshua Bengio, Joseph P. Turian

Neural Comput., 2010

Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion.

Pascal Vincent, Hugo Larochelle, Isabelle Lajoie, Yoshua Bengio, Pierre-Antoine Manzagol

J. Mach. Learn. Res., 2010

Efficient Learning of Deep Boltzmann Machines.

Ruslan Salakhutdinov, Hugo Larochelle

Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Learning to combine foveal glimpses with a third-order Boltzmann machine.

Hugo Larochelle, Geoffrey E. Hinton

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

2009

Deep Learning using Robust Interdependent Codes.

Hugo Larochelle, Dumitru Erhan, Pascal Vincent

Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Exploring Strategies for Training Deep Neural Networks.

Hugo Larochelle, Yoshua Bengio, Jérôme Louradour, Pascal Lamblin

J. Mach. Learn. Res., 2009

2008

Extracting and composing robust features with denoising autoencoders.

Pascal Vincent, Hugo Larochelle, Yoshua Bengio, Pierre-Antoine Manzagol

Proceedings of the Machine Learning, 2008

Classification using discriminative restricted Boltzmann machines.

Hugo Larochelle, Yoshua Bengio

Proceedings of the Machine Learning, 2008

Zero-data Learning of New Tasks.

Hugo Larochelle, Dumitru Erhan, Yoshua Bengio

Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008

2007

An empirical evaluation of deep architectures on problems with many factors of variation.

Hugo Larochelle, Dumitru Erhan, Aaron C. Courville, James Bergstra, Yoshua Bengio

Proceedings of the Machine Learning, 2007

2006

Nonlocal Estimation of Manifold Structure.

Yoshua Bengio, Martin Monperrus, Hugo Larochelle

Neural Comput., 2006

Greedy Layer-Wise Training of Deep Networks.

Yoshua Bengio, Pascal Lamblin, Dan Popovici, Hugo Larochelle

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

2005

Non-Local Manifold Parzen Windows.

Yoshua Bengio, Hugo Larochelle, Pascal Vincent

Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005