Pascal Vincent

According to our database, Pascal Vincent authored at least 115 papers between 1990 and 2023.

Collaborative distances:

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

2023

WorldSense: A Synthetic Benchmark for Grounded Reasoning in Large Language Models.

Youssef Benchekroun, Megi Dervishi, Mark Ibrahim, Jean-Baptiste Gaya, Xavier Martinet, Grégoire Mialon, Thomas Scialom, Emmanuel Dupoux, Dieuwke Hupkes, Pascal Vincent

CoRR, 2023

Self-Supervised Disentanglement by Leveraging Structure in Data Augmentations.

Cian Eastwood, Julius von Kügelgen, Linus Ericsson, Diane Bouchacourt, Pascal Vincent, Bernhard Schölkopf, Mark Ibrahim

CoRR, 2023

Motif: Intrinsic Motivation from Artificial Intelligence Feedback.

Martin Klissarov, Pierluca D'Oro, Shagun Sodhani, Roberta Raileanu, Pierre-Luc Bacon, Pascal Vincent, Amy Zhang, Mikael Henaff

CoRR, 2023

Discovering environments with XRM.

Mohammad Pezeshki, Diane Bouchacourt, Mark Ibrahim, Nicolas Ballas, Pascal Vincent, David Lopez-Paz

CoRR, 2023

Predicting masked tokens in stochastic locations improves masked image modeling.

Amir Bar, Florian Bordes, Assaf Shocher, Mahmoud Assran, Pascal Vincent, Nicolas Ballas, Trevor Darrell, Amir Globerson, Yann LeCun

CoRR, 2023

Identifiability of Discretized Latent Coordinate Systems via Density Landmarks Detection.

Vitória Barin Pacela, Kartik Ahuja, Simon Lacoste-Julien, Pascal Vincent

CoRR, 2023

Objectives Matter: Understanding the Impact of Self-Supervised Objectives on Vision Transformer Representations.

Shashank Shekhar, Florian Bordes, Pascal Vincent, Ari Morcos

CoRR, 2023

A surprisingly simple technique to control the pretraining bias for better transfer: Expand or Narrow your representation.

Florian Bordes, Samuel Lavoie, Randall Balestriero, Nicolas Ballas, Pascal Vincent

CoRR, 2023

Instance-Conditioned GAN Data Augmentation for Representation Learning.

Pietro Astolfi, Arantxa Casanova, Jakob Verbeek, Pascal Vincent, Adriana Romero-Soriano, Michal Drozdzal

CoRR, 2023

Towards Democratizing Joint-Embedding Self-Supervised Learning.

Florian Bordes, Randall Balestriero, Pascal Vincent

CoRR, 2023

Do SSL Models Have Déjà Vu? A Case of Unintended Memorization in Self-supervised Learning.

Casey Meehan, Florian Bordes, Pascal Vincent, Kamalika Chaudhuri, Chuan Guo

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

PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning.

Florian Bordes, Shashank Shekhar, Mark Ibrahim, Diane Bouchacourt, Pascal Vincent, Ari Morcos

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

Disentanglement of Correlated Factors via Hausdorff Factorized Support.

Karsten Roth, Mark Ibrahim, Zeynep Akata, Pascal Vincent, Diane Bouchacourt

Proceedings of the Eleventh International Conference on Learning Representations, 2023

ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations.

Badr Youbi Idrissi, Diane Bouchacourt, Randall Balestriero, Ivan Evtimov, Caner Hazirbas, Nicolas Ballas, Pascal Vincent, Michal Drozdzal, David Lopez-Paz, Mark Ibrahim

Proceedings of the Eleventh International Conference on Learning Representations, 2023

The hidden uniform cluster prior in self-supervised learning.

Mido Assran, Randall Balestriero, Quentin Duval, Florian Bordes, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Michael G. Rabbat, Nicolas Ballas

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture.

Mahmoud Assran, Quentin Duval, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Michael G. Rabbat, Yann LeCun, Nicolas Ballas

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

High Fidelity Visualization of What Your Self-Supervised Representation Knows About.

Florian Bordes, Randall Balestriero, Pascal Vincent

Trans. Mach. Learn. Res., 2022

The Emergence of Argument Structure in Artificial Languages.

Tom Bosc, Pascal Vincent

Trans. Assoc. Comput. Linguistics, 2022

The Hidden Uniform Cluster Prior in Self-Supervised Learning.

Mahmoud Assran, Randall Balestriero, Quentin Duval, Florian Bordes, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Michael G. Rabbat, Nicolas Ballas

CoRR, 2022

Guillotine Regularization: Improving Deep Networks Generalization by Removing their Head.

Florian Bordes, Randall Balestriero, Quentin Garrido, Adrien Bardes, Pascal Vincent

CoRR, 2022

Online Adversarial Attacks.

Andjela Mladenovic, Avishek Joey Bose, Hugo Berard, William L. Hamilton, Simon Lacoste-Julien, Pascal Vincent, Gauthier Gidel

Proceedings of the Tenth International Conference on Learning Representations, 2022

Understanding Dimensional Collapse in Contrastive Self-supervised Learning.

Li Jing, Pascal Vincent, Yann LeCun, Yuandong Tian

Proceedings of the Tenth International Conference on Learning Representations, 2022

Masked Siamese Networks for Label-Efficient Learning.

Mahmoud Assran, Mathilde Caron, Ishan Misra, Piotr Bojanowski, Florian Bordes, Pascal Vincent, Armand Joulin, Mike Rabbat, Nicolas Ballas

Proceedings of the Computer Vision - ECCV 2022, 2022

2021

Accounting for Variance in Machine Learning Benchmarks.

Xavier Bouthillier, Pierre Delaunay, Mirko Bronzi, Assya Trofimov, Brennan Nichyporuk, Justin Szeto, Naz Sepah, Edward Raff, Kanika Madan, Vikram Voleti, Samira Ebrahimi Kahou, Vincent Michalski, Dmitriy Serdyuk, Tal Arbel, Chris Pal, Gaël Varoquaux, Pascal Vincent

CoRR, 2021

Accounting for Variance in Machine Learning Benchmarks.

Xavier Bouthillier, Pierre Delaunay, Mirko Bronzi, Assya Trofimov, Brennan Nichyporuk, Justin Szeto, Nazanin Mohammadi Sepahvand, Edward Raff, Kanika Madan, Vikram Voleti, Samira Ebrahimi Kahou, Vincent Michalski, Tal Arbel, Chris Pal, Gaël Varoquaux, Pascal Vincent

Proceedings of Machine Learning and Systems 2021, 2021

Implicit Regularization via Neural Feature Alignment.

Aristide Baratin, Thomas George, César Laurent, R. Devon Hjelm, Guillaume Lajoie, Pascal Vincent, Simon Lacoste-Julien

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Efficient Learning in Non-Stationary Linear Markov Decision Processes.

Ahmed Touati, Pascal Vincent

CoRR, 2020

Implicit Regularization in Deep Learning: A View from Function Space.

Aristide Baratin, Thomas George, César Laurent, R. Devon Hjelm, Guillaume Lajoie, Pascal Vincent, Simon Lacoste-Julien

CoRR, 2020

Sharp Analysis of Smoothed Bellman Error Embedding.

Ahmed Touati, Pascal Vincent

CoRR, 2020

Revisiting Loss Modelling for Unstructured Pruning.

César Laurent, Camille Ballas, Thomas George, Nicolas Ballas, Pascal Vincent

CoRR, 2020

Stable Policy Optimization via Off-Policy Divergence Regularization.

Ahmed Touati, Amy Zhang, Joelle Pineau, Pascal Vincent

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Adversarial Example Games.

Avishek Joey Bose, Gauthier Gidel, Hugo Berard, Andre Cianflone, Pascal Vincent, Simon Lacoste-Julien, William L. Hamilton

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

SVRG for Policy Evaluation with Fewer Gradient Evaluations.

Zilun Peng, Ahmed Touati, Pascal Vincent, Doina Precup

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Stochastic Hamiltonian Gradient Methods for Smooth Games.

Nicolas Loizou, Hugo Berard, Alexia Jolicoeur-Martineau, Pascal Vincent, Simon Lacoste-Julien, Ioannis Mitliagkas

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

A Closer Look at the Optimization Landscapes of Generative Adversarial Networks.

Hugo Berard, Gauthier Gidel, Amjad Almahairi, Pascal Vincent, Simon Lacoste-Julien

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

Do sequence-to-sequence VAEs learn global features of sentences?

Tom Bosc, Pascal Vincent

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Stochastic Neural Network with Kronecker Flow.

Chin-Wei Huang, Ahmed Touati, Pascal Vincent, Gintare Karolina Dziugaite, Alexandre Lacoste, Aaron C. Courville

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

An Empirical Study of Batch Normalization and Group Normalization in Conditional Computation.

Vincent Michalski, Vikram Voleti, Samira Ebrahimi Kahou, Anthony Ortiz, Pascal Vincent, Chris Pal, Doina Precup

CoRR, 2019

Randomized Value Functions via Multiplicative Normalizing Flows.

Ahmed Touati, Harsh Satija, Joshua Romoff, Joelle Pineau, Pascal Vincent

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Unreproducible Research is Reproducible.

Xavier Bouthillier, César Laurent, Pascal Vincent

Proceedings of the 36th International Conference on Machine Learning, 2019

A Variational Inequality Perspective on Generative Adversarial Networks.

Gauthier Gidel, Hugo Berard, Gaëtan Vignoud, Pascal Vincent, Simon Lacoste-Julien

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

Reducing Uncertainty in Undersampled MRI Reconstruction With Active Acquisition.

Zizhao Zhang, Adriana Romero, Matthew J. Muckley, Pascal Vincent, Lin Yang, Michal Drozdzal

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

fastMRI: An Open Dataset and Benchmarks for Accelerated MRI.

Jure Zbontar, Florian Knoll, Anuroop Sriram, Matthew J. Muckley, Mary Bruno, Aaron Defazio, Marc Parente, Krzysztof J. Geras, Joe Katsnelson, Hersh Chandarana, Zizhao Zhang, Michal Drozdzal, Adriana Romero, Michael G. Rabbat, Pascal Vincent, James Pinkerton, Duo Wang, Nafissa Yakubova, Erich Owens, C. Lawrence Zitnick, Michael P. Recht, Daniel K. Sodickson, Yvonne W. Lui

CoRR, 2018

A Variational Inequality Perspective on Generative Adversarial Nets.

Gauthier Gidel, Hugo Berard, Pascal Vincent, Simon Lacoste-Julien

CoRR, 2018

Fast Approximate Natural Gradient Descent in a Kronecker Factored Eigenbasis.

Thomas George, César Laurent, Xavier Bouthillier, Nicolas Ballas, Pascal Vincent

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Convergent TREE BACKUP and RETRACE with Function Approximation.

Ahmed Touati, Pierre-Luc Bacon, Doina Precup, Pascal Vincent

Proceedings of the 35th International Conference on Machine Learning, 2018

An Evaluation of Fisher Approximations Beyond Kronecker Factorization.

César Laurent, Thomas George, Xavier Bouthillier, Nicolas Ballas, Pascal Vincent

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

Parametric Adversarial Divergences are Good Task Losses for Generative Modeling.

Gabriel Huang, Hugo Berard, Ahmed Touati, Gauthier Gidel, Pascal Vincent, Simon Lacoste-Julien

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

Auto-Encoding Dictionary Definitions into Consistent Word Embeddings.

Tom Bosc, Pascal Vincent

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

Improving Landmark Localization With Semi-Supervised Learning.

Sina Honari, Pavlo Molchanov, Stephen Tyree, Pascal Vincent, Christopher J. Pal, Jan Kautz

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017

Learning to Compute Word Embeddings On the Fly.

Dzmitry Bahdanau, Tom Bosc, Stanislaw Jastrzebski, Edward Grefenstette, Pascal Vincent, Yoshua Bengio

CoRR, 2017

Recurrent Normalization Propagation.

César Laurent, Nicolas Ballas, Pascal Vincent

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

Learning to Generate Samples from Noise through Infusion Training.

Florian Bordes, Sina Honari, Pascal Vincent

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

RATM: Recurrent Attentive Tracking Model.

Samira Ebrahimi Kahou, Vincent Michalski, Roland Memisevic, Christopher Joseph Pal, Pascal Vincent

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

2016

EmoNets: Multimodal deep learning approaches for emotion recognition in video.

Samira Ebrahimi Kahou, Xavier Bouthillier, Pascal Lamblin, Çaglar Gülçehre, Vincent Michalski, Kishore Konda, Sébastien Jean, Pierre Froumenty, Yann N. Dauphin, Nicolas Boulanger-Lewandowski, Raul Chandias Ferrari, Mehdi Mirza, David Warde-Farley, Aaron C. Courville, Pascal Vincent, Roland Memisevic, Christopher Joseph Pal, Yoshua Bengio

J. Multimodal User Interfaces, 2016

Exact gradient updates in time independent of output size for the spherical loss family.

Pascal Vincent, Alexandre de Brébisson, Xavier Bouthillier

CoRR, 2016

Hierarchical Memory Networks.

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

CoRR, 2016

The Z-loss: a shift and scale invariant classification loss belonging to the Spherical Family.

Alexandre de Brébisson, Pascal Vincent

CoRR, 2016

A Cheap Linear Attention Mechanism with Fast Lookups and Fixed-Size Representations.

Alexandre de Brébisson, Pascal Vincent

CoRR, 2016

An Exploration of Softmax Alternatives Belonging to the Spherical Loss Family.

Alexandre de Brébisson, Pascal Vincent

Proceedings of the 4th International Conference on Learning Representations, 2016

Theano: A Python framework for fast computation of mathematical expressions.

Rami Al-Rfou, Guillaume Alain, Amjad Almahairi, Christof Angermüller, Dzmitry Bahdanau, Nicolas Ballas, Frédéric Bastien, Justin Bayer, Anatoly Belikov, Alexander Belopolsky, Yoshua Bengio, Arnaud Bergeron, James Bergstra, Valentin Bisson, Josh Bleecher Snyder, Nicolas Bouchard, Nicolas Boulanger-Lewandowski, Xavier Bouthillier, Alexandre de Brébisson, Olivier Breuleux, Pierre Luc Carrier, Kyunghyun Cho, Jan Chorowski, Paul F. Christiano, Tim Cooijmans, Marc-Alexandre Côté, Myriam Côté, Aaron C. Courville, Yann N. Dauphin, Olivier Delalleau, Julien Demouth, Guillaume Desjardins, Sander Dieleman, Laurent Dinh, Melanie Ducoffe, Vincent Dumoulin, Samira Ebrahimi Kahou, Dumitru Erhan, Ziye Fan, Orhan Firat, Mathieu Germain, Xavier Glorot, Ian J. Goodfellow, Matthew Graham, Çaglar Gülçehre, Philippe Hamel, Iban Harlouchet, Jean-Philippe Heng, Balázs Hidasi, Sina Honari, Arjun Jain, Sébastien Jean, Kai Jia, Mikhail Korobov, Vivek Kulkarni, Alex Lamb, Pascal Lamblin, Eric Larsen, César Laurent, Sean Lee, Simon Lefrançois, Simon Lemieux, Nicholas Léonard, Zhouhan Lin, Jesse A. Livezey, Cory Lorenz, Jeremiah Lowin, Qianli Ma, Pierre-Antoine Manzagol, Olivier Mastropietro, Robert McGibbon, Roland Memisevic, Bart van Merriënboer, Vincent Michalski, Mehdi Mirza, Alberto Orlandi, Christopher Joseph Pal, Razvan Pascanu, Mohammad Pezeshki, Colin Raffel, Daniel Renshaw, Matthew Rocklin, Adriana Romero, Markus Roth, Peter Sadowski, John Salvatier, François Savard, Jan Schlüter, John Schulman, Gabriel Schwartz, Iulian Vlad Serban, Dmitriy Serdyuk, Samira Shabanian, Étienne Simon, Sigurd Spieckermann, S. Ramana Subramanyam, Jakub Sygnowski, Jérémie Tanguay, Gijs van Tulder, Joseph P. Turian, Sebastian Urban, Pascal Vincent, Francesco Visin, Harm de Vries, David Warde-Farley, Dustin J. Webb, Matthew Willson, Kelvin Xu, Lijun Xue, Li Yao, Saizheng Zhang, Ying Zhang

CoRR, 2016

Recombinator Networks: Learning Coarse-to-Fine Feature Aggregation.

Sina Honari, Jason Yosinski, Pascal Vincent, Christopher J. Pal

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015

Efficient Exact Gradient Update for training Deep Networks with Very Large Sparse Targets.

Pascal Vincent

Proceedings of the 3rd International Conference on Learning Representations, 2015

Dropout as data augmentation.

Kishore Reddy Konda, Xavier Bouthillier, Roland Memisevic, Pascal Vincent

CoRR, 2015

Clustering is Efficient for Approximate Maximum Inner Product Search.

Alex Auvolat, Pascal Vincent

CoRR, 2015

GSNs : Generative Stochastic Networks.

Guillaume Alain, Yoshua Bengio, Li Yao, Jason Yosinski, Eric Thibodeau-Laufer, Saizheng Zhang, Pascal Vincent

CoRR, 2015

Artificial Neural Networks Applied to Taxi Destination Prediction.

Alexandre de Brébisson, Étienne Simon, Alex Auvolat, Pascal Vincent, Yoshua Bengio

Proceedings of the ECML/PKDD 2015 Discovery Challenges co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2015), 2015

Efficient Exact Gradient Update for training Deep Networks with Very Large Sparse Targets.

Pascal Vincent, Alexandre de Brébisson, Xavier Bouthillier

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2013

Representation Learning: A Review and New Perspectives.

Yoshua Bengio, Aaron C. Courville, Pascal Vincent

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

Generalized Denoising Auto-Encoders as Generative Models.

Yoshua Bengio, Li Yao, Guillaume Alain, Pascal Vincent

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

Audio Chord Recognition with Recurrent Neural Networks.

Nicolas Boulanger-Lewandowski, Yoshua Bengio, Pascal Vincent

Proceedings of the 14th International Society for Music Information Retrieval Conference, 2013

Unsupervised Learning of Semantics of Object Detections for Scene Categorization.

Grégoire Mesnil, Salah Rifai, Antoine Bordes, Xavier Glorot, Yoshua Bengio, Pascal Vincent

Proceedings of the Pattern Recognition Applications and Methods - International Conference, 2013

Unsupervised and Transfer Learning under Uncertainty - From Object Detections to Scene Categorization.

Grégoire Mesnil, Salah Rifai, Antoine Bordes, Xavier Glorot, Yoshua Bengio, Pascal Vincent

Proceedings of the ICPRAM 2013, 2013

Semi Supervised Autoencoders: Better Focusing Model Capacity during Feature Extraction.

Hani Almousli, Pascal Vincent

Proceedings of the Neural Information Processing - 20th International Conference, 2013

Combining modality specific deep neural networks for emotion recognition in video.

Samira Ebrahimi Kahou, Christopher J. Pal, Xavier Bouthillier, Pierre Froumenty, Çaglar Gülçehre, Roland Memisevic, Pascal Vincent, Aaron C. Courville, Yoshua Bengio, Raul Chandias Ferrari, Mehdi Mirza, Sébastien Jean, Pierre Luc Carrier, Yann N. Dauphin, Nicolas Boulanger-Lewandowski, Abhishek Aggarwal, Jeremie Zumer, Pascal Lamblin, Jean-Philippe Raymond, Guillaume Desjardins, Razvan Pascanu, David Warde-Farley, Atousa Torabi, Arjun Sharma, Emmanuel Bengio, Kishore Reddy Konda, Zhenzhou Wu

Proceedings of the 2013 International Conference on Multimodal Interaction, 2013

High-dimensional sequence transduction.

Nicolas Boulanger-Lewandowski, Yoshua Bengio, Pascal Vincent

Proceedings of the IEEE International Conference on Acoustics, 2013

2012

Unsupervised and Transfer Learning Challenge: a Deep Learning Approach.

Grégoire Mesnil, Yann N. Dauphin, Xavier Glorot, Salah Rifai, Yoshua Bengio, Ian J. Goodfellow, Erick Lavoie, Xavier Muller, Guillaume Desjardins, David Warde-Farley, Pascal Vincent, Aaron C. Courville, James Bergstra

Proceedings of the Unsupervised and Transfer Learning, 2012

Unsupervised Feature Learning and Deep Learning: A Review and New Perspectives

Yoshua Bengio, Aaron C. Courville, Pascal Vincent

CoRR, 2012

Discriminative Non-negative Matrix Factorization for Multiple Pitch Estimation.

Nicolas Boulanger-Lewandowski, Yoshua Bengio, Pascal Vincent

Proceedings of the 13th International Society for Music Information Retrieval Conference, 2012

A Generative Process for Contractive Auto-Encoders.

Salah Rifai, Yann N. Dauphin, Pascal Vincent, Yoshua Bengio

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

Modeling Temporal Dependencies in High-Dimensional Sequences: Application to Polyphonic Music Generation and Transcription.

Nicolas Boulanger-Lewandowski, Yoshua Bengio, Pascal Vincent

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

Disentangling Factors of Variation for Facial Expression Recognition.

Salah Rifai, Yoshua Bengio, Aaron C. Courville, Pascal Vincent, Mehdi Mirza

Proceedings of the Computer Vision - ECCV 2012, 2012

2011

A Connection Between Score Matching and Denoising Autoencoders.

Pascal Vincent

Neural Comput., 2011

Quickly Generating Representative Samples from an RBM-Derived Process.

Olivier Breuleux, Yoshua Bengio, Pascal Vincent

Neural Comput., 2011

A high-order feature synthesis and selection algorithm applied to insurance risk modelling.

Charles Dugas, Nicolas Chapados, Réjean Ducharme, Xavier Saint-Mleux, Pascal Vincent

Int. J. Bus. Intell. Data Min., 2011

Learning invariant features through local space contraction

Salah Rifai, Xavier Muller, Xavier Glorot, Grégoire Mesnil, Yoshua Bengio, Pascal Vincent

CoRR, 2011

Adding noise to the input of a model trained with a regularized objective

Salah Rifai, Xavier Glorot, Yoshua Bengio, Pascal Vincent

CoRR, 2011

Higher Order Contractive Auto-Encoder.

Salah Rifai, Grégoire Mesnil, Pascal Vincent, Xavier Muller, Yoshua Bengio, Yann N. Dauphin, Xavier Glorot

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

The Manifold Tangent Classifier.

Salah Rifai, Yann N. Dauphin, Pascal Vincent, Yoshua Bengio, Xavier Muller

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Fabrication and characterization of 100-nm wide silicon nanocantilevers using top-down approach.

Samuel Guillon, Daisuke Saya, Laurent Mazenq, Liviu Nicu, Sorin Perisanu, Pascal Vincent

Proceedings of the 6th IEEE International Conference on Nano/Micro Engineered and Molecular Systems, 2011

Contractive Auto-Encoders: Explicit Invariance During Feature Extraction.

Salah Rifai, Pascal Vincent, Xavier Muller, Xavier Glorot, Yoshua Bengio

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

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

Why Does Unsupervised Pre-training Help Deep Learning?

Dumitru Erhan, Aaron C. Courville, Yoshua Bengio, Pascal Vincent

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

Why Does Unsupervised Pre-training Help Deep Learning?

Dumitru Erhan, Yoshua Bengio, Aaron C. Courville, Pierre-Antoine Manzagol, Pascal Vincent, Samy Bengio

J. Mach. Learn. Res., 2010

Tempered Markov Chain Monte Carlo for training of Restricted Boltzmann Machines.

Guillaume Desjardins, Aaron C. Courville, Yoshua Bengio, Pascal Vincent, Olivier Delalleau

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

The Difficulty of Training Deep Architectures and the Effect of Unsupervised Pre-Training.

Dumitru Erhan, Pierre-Antoine Manzagol, Yoshua Bengio, Samy Bengio, Pascal Vincent

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

Scoring Models for Insurance Risk Sharing Pool Opimization.

Nicolas Chapados, Charles Dugas, Pascal Vincent, Réjean Ducharme

Proceedings of the Workshops Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008

2007

The Need for Open Source Software in Machine Learning.

Sören Sonnenburg, Mikio L. Braun, Cheng Soon Ong, Samy Bengio, Léon Bottou, Geoffrey Holmes, Yann LeCun, Klaus-Robert Müller, Fernando Pereira, Carl Edward Rasmussen, Gunnar Rätsch, Bernhard Schölkopf, Alexander J. Smola, Pascal Vincent, Jason Weston, Robert C. Williamson

J. Mach. Learn. Res., 2007

2006

Spectral Dimensionality Reduction.

Yoshua Bengio, Olivier Delalleau, Nicolas Le Roux, Jean-François Paiement, Pascal Vincent, Marie Ouimet

Proceedings of the Feature Extraction - Foundations and Applications, 2006

2005

Convex Neural Networks.

Yoshua Bengio, Nicolas Le Roux, Pascal Vincent, Olivier Delalleau, Patrice Marcotte

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

2004

Learning Eigenfunctions Links Spectral Embedding and Kernel PCA.

Yoshua Bengio, Olivier Delalleau, Nicolas Le Roux, Jean-François Paiement, Pascal Vincent, Marie Ouimet

Neural Comput., 2004

2003

A Neural Probabilistic Language Model.

Yoshua Bengio, Réjean Ducharme, Pascal Vincent, Christian Janvin

J. Mach. Learn. Res., 2003

Out-of-Sample Extensions for LLE, Isomap, MDS, Eigenmaps, and Spectral Clustering.

Yoshua Bengio, Jean-François Paiement, Pascal Vincent, Olivier Delalleau, Nicolas Le Roux, Marie Ouimet

Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

2002

Kernel Matching Pursuit.

Pascal Vincent, Yoshua Bengio

Mach. Learn., 2002

Manifold Parzen Windows.

Pascal Vincent, Yoshua Bengio

Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

2001

ROBOSIX UPMC-CFA: RoboCup Team Description.

Ryad Benosman, Francis Bras, Frederic Bach, Simon Boulay, Emmanuelle Cahn, Sylvain Come, Gilles Cordurié, Jarlegan Marie Annick, Lapied Loic, Cyrille Potereau, Franck Richard, Samedi Sath, Xavier Vasseur, Pascal Vincent

Proceedings of the RoboCup 2001: Robot Soccer World Cup V, 2001

K-Local Hyperplane and Convex Distance Nearest Neighbor Algorithms.

Pascal Vincent, Yoshua Bengio

Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Estimating Car Insurance Premia: a Case Study in High-Dimensional Data Inference.

Nicolas Chapados, Yoshua Bengio, Pascal Vincent, Joumana Ghosn, Charles Dugas, Ichiro Takeuchi, Linyan Meng

Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

2000

A Neural Probabilistic Language Model.

Yoshua Bengio, Réjean Ducharme, Pascal Vincent

Proceedings of the Advances in Neural Information Processing Systems 13, 2000

A Neural Support Vector Network Architecture with Adaptive Kernels.

Pascal Vincent, Yoshua Bengio

Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000

1999

Color Documents on the Web with DJVU.

Patrick Haffner, Yann LeCun, Léon Bottou, Paul G. Howard, Pascal Vincent, Bill Riemers

Proceedings of the 1999 International Conference on Image Processing, 1999

1990

Region Tracking through Neural Classifier.

Patrick Thévenoux, Pascal Vincent

Proceedings of IAPR Workshop on Machine Vision Applications, 1990