Vincent, Pascal

71 publications

ICML 2025 Compositional Risk Minimization Divyat Mahajan, Mohammad Pezeshki, Charles Arnal, Ioannis Mitliagkas, Kartik Ahuja, Pascal Vincent

ICLR 2025 MaestroMotif: Skill Design from Artificial Intelligence Feedback Martin Klissarov, Mikael Henaff, Roberta Raileanu, Shagun Sodhani, Pascal Vincent, Amy Zhang, Pierre-Luc Bacon, Doina Precup, Marlos C. Machado, Pierluca D'Oro

ICLR 2025 The Pitfalls of Memorization: When Memorization Hurts Generalization Reza Bayat, Mohammad Pezeshki, Elvis Dohmatob, David Lopez-Paz, Pascal Vincent

NeurIPSW 2024 Compositional Risk Minimization Divyat Mahajan, Mohammad Pezeshki, Ioannis Mitliagkas, Kartik Ahuja, Pascal Vincent

ICML 2024 Discovering Environments with XRM Mohammad Pezeshki, Diane Bouchacourt, Mark Ibrahim, Nicolas Ballas, Pascal Vincent, David Lopez-Paz

ICLR 2024 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

CLeaR 2024 On the Identifiability of Quantized Factors Vitória Barin-Pacela, Kartik Ahuja, Simon Lacoste-Julien, Pascal Vincent

ICML 2024 Stochastic Positional Embeddings Improve Masked Image Modeling Amir Bar, Florian Bordes, Assaf Shocher, Mido Assran, Pascal Vincent, Nicolas Ballas, Trevor Darrell, Amir Globerson, Yann Lecun

NeurIPSW 2024 The Pitfalls of Memorization: When Memorization Hinders Generalization Reza Bayat, Mohammad Pezeshki, Elvis Dohmatob, David Lopez-Paz, Pascal Vincent

NeurIPSW 2023 Discovering Environments with XRM Mohammad Pezeshki, Diane Bouchacourt, Mark Ibrahim, Nicolas Ballas, Pascal Vincent, David Lopez-Paz

ICLR 2023 Disentanglement of Correlated Factors via Hausdorff Factorized Support Karsten Roth, Mark Ibrahim, Zeynep Akata, Pascal Vincent, Diane Bouchacourt

NeurIPS 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

TMLR 2023 Guillotine Regularization: Why Removing Layers Is Needed to Improve Generalization in Self-Supervised Learning Florian Bordes, Randall Balestriero, Quentin Garrido, Adrien Bardes, Pascal Vincent

ICMLW 2023 Identifiability of Discretized Latent Coordinate Systems via Density Landmarks Detection Vitória Barin-Pacela, Kartik Ahuja, Simon Lacoste-Julien, Pascal Vincent

ICMLW 2023 Identifiability of Discretized Latent Coordinate Systems via Density Landmarks Detection Vitória Barin-Pacela, Kartik Ahuja, Simon Lacoste-Julien, Pascal Vincent

ICLR 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

NeurIPSW 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

NeurIPSW 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

ICLRW 2023 Objectives Matter: Understanding the Impact of Self-Supervised Objectives on Vision Transformer Representations Shashank Shekhar, Florian Bordes, Pascal Vincent, Ari S. Morcos

NeurIPS 2023 PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning Florian Bordes, Shashank Shekhar, Mark Ibrahim, Diane Bouchacourt, Pascal Vincent, Ari Morcos

NeurIPSW 2023 Self-Supervised Disentanglement by Leveraging Structure in Data Augmentations Cian Eastwood, Julius von Kügelgen, Linus Ericsson, Diane Bouchacourt, Pascal Vincent, Mark Ibrahim, Bernhard Schölkopf

CVPR 2023 Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture Mahmoud Assran, Quentin Duval, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Michael Rabbat, Yann LeCun, Nicolas Ballas

ICLR 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 Rabbat, Nicolas Ballas

TMLR 2022 High Fidelity Visualization of What Your Self-Supervised Representation Knows About Florian Bordes, Randall Balestriero, Pascal Vincent

ECCV 2022 Masked Siamese Networks for Label-Efficient Learning Mahmoud Assran, Mathilde Caron, Ishan Misra, Piotr Bojanowski, Florian Bordes, Pascal Vincent, Armand Joulin, Michael Rabbat, Nicolas Ballas

ICLR 2022 Online Adversarial Attacks Andjela Mladenovic, Joey Bose, Hugo Berard, William L. Hamilton, Simon Lacoste-Julien, Pascal Vincent, Gauthier Gidel

ICLR 2022 Understanding Dimensional Collapse in Contrastive Self-Supervised Learning Li Jing, Pascal Vincent, Yann LeCun, Yuandong Tian

AISTATS 2021 Implicit Regularization via Neural Feature Alignment Aristide Baratin, Thomas George, César Laurent, R Devon Hjelm, Guillaume Lajoie, Pascal Vincent, Simon Lacoste-Julien

ICLR 2020 A Closer Look at the Optimization Landscapes of Generative Adversarial Networks Hugo Berard, Gauthier Gidel, Amjad Almahairi, Pascal Vincent, Simon Lacoste-Julien

NeurIPS 2020 Adversarial Example Games Joey Bose, Gauthier Gidel, Hugo Berard, Andre Cianflone, Pascal Vincent, Simon Lacoste-Julien, Will Hamilton

NeurIPSW 2020 Implicit Regularization via Neural Feature Alignment Aristide Baratin, Thomas George, César Laurent, R Devon Hjelm, Guillaume Lajoie, Pascal Vincent, Simon Lacoste-Julien

IJCAI 2020 SVRG for Policy Evaluation with Fewer Gradient Evaluations Zilun Peng, Ahmed Touati, Pascal Vincent, Doina Precup

UAI 2020 Stable Policy Optimization via Off-Policy Divergence Regularization Ahmed Touati, Amy Zhang, Joelle Pineau, Pascal Vincent

ICML 2020 Stochastic Hamiltonian Gradient Methods for Smooth Games Nicolas Loizou, Hugo Berard, Alexia Jolicoeur-Martineau, Pascal Vincent, Simon Lacoste-Julien, Ioannis Mitliagkas

AISTATS 2020 Stochastic Neural Network with Kronecker Flow Chin-Wei Huang, Ahmed Touati, Pascal Vincent, Gintare Karolina Dziugaite, Alexandre Lacoste, Aaron Courville

ICLR 2019 A Variational Inequality Perspective on Generative Adversarial Networks Gauthier Gidel, Hugo Berard, Gaëtan Vignoud, Pascal Vincent, Simon Lacoste-Julien

UAI 2019 Randomized Value Functions via Multiplicative Normalizing Flows Ahmed Touati, Harsh Satija, Joshua Romoff, Joelle Pineau, Pascal Vincent

ICML 2019 Unreproducible Research Is Reproducible Xavier Bouthillier, César Laurent, Pascal Vincent

ICML 2018 Convergent Tree Backup and Retrace with Function Approximation Ahmed Touati, Pierre-Luc Bacon, Doina Precup, Pascal Vincent

NeurIPS 2018 Fast Approximate Natural Gradient Descent in a Kronecker Factored Eigenbasis Thomas George, César Laurent, Xavier Bouthillier, Nicolas Ballas, Pascal Vincent

ICLR 2017 Learning to Generate Samples from Noise Through Infusion Training Florian Bordes, Sina Honari, Pascal Vincent

CVPRW 2017 RATM: Recurrent Attentive Tracking Model Samira Ebrahimi Kahou, Vincent Michalski, Roland Memisevic, Christopher Joseph Pal, Pascal Vincent

ICLR 2017 Recurrent Normalization Propagation César Laurent, Nicolas Ballas, Pascal Vincent

ICLR 2016 An Exploration of SoftMax Alternatives Belonging to the Spherical Loss Family Alexandre de Brébisson, Pascal Vincent

CVPR 2016 Recombinator Networks: Learning Coarse-to-Fine Feature Aggregation Sina Honari, Jason Yosinski, Pascal Vincent, Christopher Pal

NeurIPS 2015 Efficient Exact Gradient Update for Training Deep Networks with Very Large Sparse Targets Pascal Vincent, Alexandre de Brébisson, Xavier Bouthillier

ICLR 2015 Efficient Exact Gradient Update for Training Deep Networks with Very Large Sparse Targets Pascal Vincent

NeurIPS 2013 Generalized Denoising Auto-Encoders as Generative Models Yoshua Bengio, Li Yao, Guillaume Alain, Pascal Vincent

ICML 2012 A Generative Process for Contractive Auto-Encoders Salah Rifai, Yann N. Dauphin, Pascal Vincent, Yoshua Bengio

ECCV 2012 Disentangling Factors of Variation for Facial Expression Recognition Salah Rifai, Yoshua Bengio, Aaron C. Courville, Pascal Vincent, Mehdi Mirza

ICML 2012 Modeling Temporal Dependencies in High-Dimensional Sequences: Application to Polyphonic Music Generation and Transcription Nicolas Boulanger-Lewandowski, Yoshua Bengio, Pascal Vincent

ICML 2011 Contractive Auto-Encoders: Explicit Invariance During Feature Extraction Salah Rifai, Pascal Vincent, Xavier Muller, Xavier Glorot, Yoshua Bengio

ECML-PKDD 2011 Higher Order Contractive Auto-Encoder Salah Rifai, Grégoire Mesnil, Pascal Vincent, Xavier Muller, Yoshua Bengio, Yann N. Dauphin, Xavier Glorot

NeurIPS 2011 The Manifold Tangent Classifier Salah Rifai, Yann N. Dauphin, Pascal Vincent, Yoshua Bengio, Xavier Muller

JMLR 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

AISTATS 2010 Tempered Markov Chain Monte Carlo for Training of Restricted Boltzmann Machines Guillaume Desjardins, Aaron Courville, Yoshua Bengio, Pascal Vincent, Olivier Delalleau

JMLR 2010 Why Does Unsupervised Pre-Training Help Deep Learning? Dumitru Erhan, Yoshua Bengio, Aaron Courville, Pierre-Antoine Manzagol, Pascal Vincent, Samy Bengio

AISTATS 2010 Why Does Unsupervised Pre-Training Help Deep Learning? Dumitru Erhan, Aaron Courville, Yoshua Bengio, Pascal Vincent

AISTATS 2009 Deep Learning Using Robust Interdependent Codes Hugo Larochelle, Dumitru Erhan, Pascal Vincent

AISTATS 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

ICML 2008 Extracting and Composing Robust Features with Denoising Autoencoders Pascal Vincent, Hugo Larochelle, Yoshua Bengio, Pierre-Antoine Manzagol

JMLR 2007 The Need for Open Source Software in Machine Learning Sören Sonnenburg, Mikio L. Braun, Cheng Soon Ong, Samy Bengio, Leon Bottou, Geoffrey Holmes, Yann LeCun, Klaus-Robert Müller, Fernando Pereira, Carl Edward Rasmussen, Gunnar Rätsch, Bernhard Schölkopf, Alexander Smola, Pascal Vincent, Jason Weston, Robert Williamson

NeurIPS 2005 Convex Neural Networks Yoshua Bengio, Nicolas L. Roux, Pascal Vincent, Olivier Delalleau, Patrice Marcotte

NeurIPS 2005 Non-Local Manifold Parzen Windows Yoshua Bengio, Hugo Larochelle, Pascal Vincent

NeCo 2004 Learning Eigenfunctions Links Spectral Embedding and Kernel PCA Yoshua Bengio, Olivier Delalleau, Nicolas Le Roux, Jean-François Paiement, Pascal Vincent, Marie Ouimet

NeurIPS 2003 Out-of-Sample Extensions for LLE, Isomap, MDS, Eigenmaps, and Spectral Clustering Yoshua Bengio, Jean-françcois Paiement, Pascal Vincent, Olivier Delalleau, Nicolas L. Roux, Marie Ouimet

MLJ 2002 Kernel Matching Pursuit Pascal Vincent, Yoshua Bengio

NeurIPS 2002 Manifold Parzen Windows Pascal Vincent, Yoshua Bengio

NeurIPS 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

NeurIPS 2001 K-Local Hyperplane and Convex Distance Nearest Neighbor Algorithms Pascal Vincent, Yoshua Bengio

NeurIPS 2000 A Neural Probabilistic Language Model Yoshua Bengio, Réjean Ducharme, Pascal Vincent