Journal papers

  • Movie Description [link]
    Anna Rohrbach, Atousa Torabi, Marcus Rohrbach, Niket Tandon, Christopher Pal, Hugo Larochelle, Aaron Courville and Bernt Schiele,
    International Journal of Computer Vision, 1-27, 2017

  • Neural Autoregressive Distribution Estimation [pdf]
    Benigno Uria, Marc-Alexandre Côté, Karol Gregor, Iain Murray and Hugo Larochelle,
    Journal of Machine Learning Research, 17(205): 1-37, 2016

  • An Infinite Restricted Boltzmann Machine [pdf] [arxiv]
    Marc-Alexandre Côté and Hugo Larochelle,
    Neural Computation, 28(7): 1265-1288, 2016

  • Domain-Adversarial Training of Neural Networks [pdf]
    Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan, Pascal Germain, Hugo Larochelle, François Laviolette, Mario Marchand and Victor Lempitsky,
    Journal of Machine Learning Research, 17(59): 1-35, 2016

  • Correlational Neural Networks [pdf] [arxiv]
    Sarath Chandar, Mitesh M. Khapra, Hugo Larochelle and Balaraman Ravindran,
    Neural Computation, 28(2): 286-304, 2016

  • A Deep and Autoregressive Approach for Topic Modeling of Multimodal Data [arxiv]
    Yin Zheng, Yu-Jin Zhang and Hugo Larochelle,
    IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(6): 1056-1069, 2016

  • Within-Brain Classification for Brain Tumor Segmentation [arxiv]
    Mohammad Havaei, Hugo Larochelle, Philippe Poulin and Pierre-Marc Jodoin,
    International Journal of Computer Assisted Radiology and Surgery, 1-12, 2015

  • A Neural Autoregressive Approach to Attention-based Recognition [pdf]
    Yin Zheng, Richard Zemel, Yu-Jin Zhang and Hugo Larochelle,
    International Journal of Computer Vision, 113(1): 67-79, 2015

  • PhenoVar: a phenotype-driven approach in clinical genomics for the diagnosis of polymalformative syndromes [html]
    Yannis J Trakadis, Caroline Buote, Jean-François Therriault, Pierre-Étienne Jacques, Hugo Larochelle and Sébastien Lévesque,
    BMC Medical Genomics, 7(22), 2014

  • Nonparametric Guidance of Autoencoder Representations using Label Information [pdf]
    Jasper Snoek, Ryan P. Adams and Hugo Larochelle,
    Journal of Machine Learning Research, 13(Sep): 2567-2588, 2012

  • Learning Where to Attend With Deep Architectures for Image Tracking [pdf] [html]
    Misha Denil, Loris Bazzani, Hugo Larochelle and Nando de Freitas,
    Neural Computation, 24(8): 2151-2184, 2012

  • Learning Algorithms for the Classification Restricted Boltzmann Machine [pdf]
    Hugo Larochelle, Michael Mandel, Razvan Pascanu and Yoshua Bengio,
    Journal of Machine Learning Research, 13(Mar): 643-669, 2012

  • Detonation Classification from Acoustic Signature with the Restricted Boltzmann Machine [pdf]
    Yoshua Bengio, Nicolas Chapados, Olivier Delalleau, Hugo Larochelle, Xavier Saint-Mleux, Christian Hudon and Jérôme Louradour,
    Computational Intelligence, 28(2): 261-288, 2012

  • Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion [pdf]
    Pascal Vincent, Hugo Larochelle, Isabelle Lajoie, Yoshua Bengio and Pierre-Antoine Manzagol,
    Journal of Machine Learning Research, 11(Dec): 3371-3408, 2010

  • Tractable Multivariate Binary Density Estimation and the Restricted Boltzmann Forest [pdf]
    Hugo Larochelle, Yoshua Bengio and Joseph Turian,
    Neural Computation, 22(9): 2285-2307, 2010

  • Exploring Strategies for Training Deep Neural Networks [pdf]
    Hugo Larochelle, Yoshua Bengio, Jérôme Louradour and Pascal Lamblin,
    Journal of Machine Learning Research, 10(Jan): 1-40, 2009

  • Non-Local Estimation of Manifold Structure [pdf] [ps]
    Yoshua Bengio, Martin Monperrus and Hugo Larochelle,
    Neural Computation, 18(10): 2509-2528, 2006

Conference Papers

  • Autoencoding beyond pixels using a learned similarity metric [pdf]
    Anders Boesen Lindbo Larsen, Søren Kaae Sønderby, Hugo Larochelle and Ole Winther,
    International Conference on Machine Learning, 2016

  • Dynamic Capacity Networks [pdf]
    Amjad Almahairi, Nicolas Ballas, Tim Cooijmans, Yin Zheng, Hugo Larochelle and Aaron Courville,
    International Conference on Machine Learning, 2016

  • Describing Videos by Exploiting Temporal Structure [arxiv]
    Li Yao, Atousa Torabi, Kyunghyun Cho, Nicolas Ballas, Christopher Pal, Hugo Larochelle and Aaron Courville,
    International Conference on Computer Vision, 2015

  • MADE: Masked Autoencoder for Distribution Estimation [pdf] [supp]
    Mathieu Germain, Karol Gregor, Iain Murray and Hugo Larochelle,
    International Conference on Machine Learning, 2015

  • Using a Recursive Neural Network to Learn an Agent's Decision Model for Plan Recognition [pdf]
    Francis Bisson, Hugo Larochelle and Froduald Kabanza,
    International Joint Conference on Artificial Intelligence, 2015

  • An Autoencoder Approach to Learning Bilingual Word Representations [pdf]
    Sarath Chandar, Stanislas Lauly, Hugo Larochelle, Mitesh M. Khapra, Balaraman Ravindran, Vikas Raykar et Amrita Saha,
    Advances in Neural Information Processing Systems 27, 2014

  • Sequential Model-Based Ensemble Optimization [pdf]
    Alexandre Lacoste, Hugo Larochelle, Mario Marchand and François Laviolette,
    Uncertainty in Artificial Intelligence, 2014

  • Leveraging user libraries to bootstrap collaborative filtering [pdf]
    Laurent Charlin, Richard Zemel and Hugo Larochelle,
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2014

  • Topic Modeling of Multimodal Data: an Autoregressive Approach [pdf]
    Yin Zheng, Yu-Jin Zhang and Hugo Larochelle,
    IEEE Conference on Computer Vision and Pattern Recognition, 2014

  • Efficient interactive brain tumor segmentation as within-brain kNN classification [pdf]
    Mohammad Havaei, Pierre-Marc Jodoin and Hugo Larochelle,
    International Conference on Pattern Recognition, 2014

  • A Deep and Tractable Density Estimator [pdf]
    Benigno Uria, Iain Murray and Hugo Larochelle,
    International Conference on Machine Learning, 2014

  • Agnostic Bayesian Learning of Ensembles [pdf]
    Alexandre Lacoste, Mario Marchand, François Laviolette and Hugo Larochelle,
    International Conference on Machine Learning, 2014

  • RNADE: The real-valued neural autoregressive density-estimator [pdf]
    Benigno Uria, Iain Murray and Hugo Larochelle,
    Advances in Neural Information Processing Systems 26, 2013

  • A Neural Autoregressive Topic Model [pdf] [supp] [code]
    Hugo Larochelle and Stanislas Lauly,
    Advances in Neural Information Processing Systems 25, 2012

  • Practical Bayesian Optimization of Machine Learning Algorithms [pdf] [supp] [code]
    Jasper Snoek, Hugo Larochelle and Ryan P. Adams,
    Advances in Neural Information Processing Systems 25, 2012

  • Learning to Rank By Aggregating Expert Preferences [pdf]
    Maksims Volkovs, Hugo Larochelle and Richard Zemel,
    International Conference on Information and Knowledge Management, 2012

  • Training Restricted Boltzmann Machines on Word Observations [pdf]
    George E. Dahl, Ryan P. Adams and Hugo Larochelle,
    International Conference on Machine Learning, 2012

  • On Nonparametric Guidance for Learning Autoencoder Representations [pdf]
    Jasper Snoek, Ryan P. Adams and Hugo Larochelle,
    Artificial Intelligence and Statistics, 2012

  • Classification of Sets using Restricted Boltzmann Machines [pdf] [supp] [arxiv]
    Jérôme Louradour and Hugo Larochelle,
    Uncertainty in Artificial Intelligence, 2011

  • Conditional Restricted Boltzmann Machines for Structured Output Prediction [pdf]
    Volodymyr Mnih, Hugo Larochelle and Geoffrey Hinton,
    Uncertainty in Artificial Intelligence, 2011

  • Learning Attentional Policies for Tracking and Recognition in Video with Deep Networks [pdf] [talk] [youtube]
    Loris Bazzani, Nando de Freitas, Hugo Larochelle, Vittorio Murino and Jo-Anne Ting,
    International Conference on Machine Learning, 2011

  • The Neural Autoregressive Distribution Estimator [pdf] [talk] [code]
    Hugo Larochelle and Iain Murray,
    Artificial Intelligence and Statistics, 2011
    Notable Paper Award

  • Learning to combine foveal glimpses with a third-order Boltzmann machine [pdf] [supp] [talk] [faces video]
    Hugo Larochelle and Geoffrey Hinton,
    Advances in Neural Information Processing Systems 23, 2010

  • Efficient Learning of Deep Boltzmann Machines [pdf][code]
    Ruslan Salakhutdinov and Hugo Larochelle,
    Artificial Intelligence and Statistics, 2010

  • Deep Learning using Robust Interdependent Codes [pdf]
    Hugo Larochelle, Dumitru Erhan and Pascal Vincent,
    Artificial Intelligence and Statistics, 2009

  • Classification using Discriminative Restricted Boltzmann Machines [pdf] [talk]
    Hugo Larochelle and Yoshua Bengio,
    International Conference on Machine Learning, 2008

  • Extracting and Composing Robust Features with Denoising Autoencoders [pdf]
    Pascal Vincent, Hugo Larochelle, Yoshua Bengio and Pierre-Antoine Manzagol,
    International Conference on Machine Learning, 2008

  • Zero-data Learning of New Tasks [pdf]
    Hugo Larochelle, Dumitru Erhan and Yoshua Bengio,
    AAAI Conference on Artificial Intelligence, 2008

  • An Empirical Evaluation of Deep Architectures on Problems with Many Factors of Variation [pdf][html]
    Hugo Larochelle, Dumitru Erhan, Aaron Courville, James Bergstra and Yoshua Bengio,
    International Conference on Machine Learning, 2007

  • Greedy Layer-Wise Training of Deep Networks [pdf]
    Yoshua Bengio, Pascal Lamblin, Dan Popovici and Hugo Larochelle,
    Advances in Neural Information Processing Systems 19, 2007

  • Non-Local Manifold Parzen Windows [pdf]
    Yoshua Bengio, Hugo Larochelle and Pascal Vincent,
    Advances in Neural Information Processing Systems 18, 2006

Thesis

  • Études de techniques d'appentissage non-supervisé pour l'amélioration de l'entraînement supervisé de modèles connexionnistes [pdf]
    Hugo Larochelle,
    Ph.D. thesis, Université de Montréal, 2009

Workshop Papers and Technical Reports

  • An Infinite Restricted Boltzmann Machine [arxiv]
    Marc-Alexandre Côté and Hugo Larochelle,
    arXiv, 2015

  • Using Descriptive Video Services to Create a Large Data Source for Video Annotation Research [arxiv]
    Atousa Torabi, Christopher Pal, Hugo Larochelle and Aaron Courville,
    arXiv, 2015

  • Learning Multilingual Word Representations using a Bag-of-Words Autoencoder [pdf] [arxiv]
    Stanislas Lauly, Alex Boulanger and Hugo Larochelle,
    NIPS Deep Learning Workshop, 2013

  • Loss-sensitive Training of Probabilistic Conditional Random Fields [arxiv]
    Maksims Volkovs, Hugo Larochelle and Richard Zemel,
    arXiv, 2011

  • Autotagging music with conditional restricted Boltzmann machines [arxiv]
    Michael Mandel, Razvan Pascanu, Hugo Larochelle and Yoshua Bengio,
    arXiv, 2011

  • Extracting and Composing Robust Features with Denoising Autoencoders [pdf]
    Pascal Vincent, Hugo Larochelle, Yoshua Bengio and Pierre-Antoine Manzagol,
    Technical Report #1316, Département d'informatique et recherche opérationnelle,
    Université de Montréal, 2008

  • Distributed Representation Prediction for Generalization to New Words [pdf]
    Hugo Larochelle and Yoshua Bengio,
    Technical Report #1284, Département d'informatique et recherche opérationnelle,
    Université de Montréal, 2006

  • Greedy Layer-Wise Training of Deep Networks [pdf]
    Yoshua Bengio, Pascal Lamblin, Dan Popovici and Hugo Larochelle,
    Technical Report #1282, Département d'informatique et recherche opérationnelle,
    Université de Montréal, 2006

  • Non-Local Manifold Parzen Windows [pdf] [ps]
    Yoshua Bengio and Hugo Larochelle,
    Technical Report #1264, Département d'informatique et recherche opérationnelle,
    Université de Montréal, 2005

 Others

  • Classification using Discriminative Restricted Boltzmann Machines [pdf]
    Hugo Larochelle and Yoshua Bengio,
    MITACS Second Canada-France Congress,
    Third place at poster competition,
    Montreal, Canada, 2008

  • Deep Woods [pdf]
    Yoshua Bengio, Hugo Larochelle and Joseph Turian,
    Poster presented at the Learning@Snowbird Workshop,
    Snowbird, USA, 2008

  • Generalization to a zero-data task: an empirical study [pdf] [ps]
    Hugo Larochelle, Dumitru Erhan and Yoshua Bengio
    Talk and poster presented at the Learning Workshop,
    San Juan, Puerto Rico, 2007

  • Didactiel sur les réseaux de neurones en traitement de la langue [pdf]
    Hugo Larochelle,
    Talk in the RALI-OLST seminar series
    Université de Montréal, 2006

  • Non-Local Manifold Parzen Windows [pdf]
    Yoshua Bengio, Hugo Larochelle and Pascal Vincent,
    Talk at the CIAR Summer School,
    University of Toronto, 2005

  • Non-Local Manifold Parzen Windows [pdf] [ps]
    Yoshua Bengio and Hugo Larochelle,
    Poster presented at the Learning@Snowbird Workshop,
    Snowbird, USA, 2005

  • Implantation et analyse d’un modèle graphique de désambiguïsation
    à entraînement supervisé, semi-supervisé et non-supervisé [pdf] [ps]

    Hugo Larochelle and Yoshua Bengio,
    IFT3051 project, Département d'informatique et recherche opérationnelle,
    Université de Montréal, 2004.

  • Some Supervised Models in Disambiguation [ppt]
    Hugo Larochelle, Christian Jauvin and Yoshua Bengio,
    Poster presented at MITACS Quebec Interchange,
    Montréal, Canada, 2003.

  • Étude de la pertinence de métriques statistiques pour la détection de termes dans un document [pdf] [ps]
    Hugo Larochelle and Philippe Langlais,
    NSERC Internship report at RALI lab,
    Département d'informatique et recherche opérationnelle,
    Université de Montréal, été 2002.