Pascal Vincent

155 papers A* 30A 8B 1C 2Misc 2Journal 78Unranked 33

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Compositional Risk Minimization. ICML Divyat Mahajan, Mohammad Pezeshki, Charles Arnal, Ioannis Mitliagkas, Kartik Ahuja, Pascal Vincent
2025	A*	`conf`	MaestroMotif: Skill Design from Artificial Intelligence Feedback. ICLR Martin Klissarov, Mikael Henaff, Roberta Raileanu, Shagun Sodhani, Pascal Vincent, Amy Zhang, Pierre-Luc Bacon, Doina Precup, Marlos C. Machado, Pierluca D'Oro
2025	J	`jnl`	Operationalizing Quantized Disentanglement. CoRR Vitória Barin Pacela, Kartik Ahuja, Simon Lacoste-Julien, Pascal Vincent
2025	J	`jnl`	Steering Large Language Model Activations in Sparse Spaces. CoRR Reza Bayat, Ali Rahimi-Kalahroudi, Mohammad Pezeshki, Sarath Chandar, Pascal Vincent
2025	A*	`conf`	The Pitfalls of Memorization: When Memorization Hurts Generalization. ICLR Reza Bayat, Mohammad Pezeshki, Elvis Dohmatob, David Lopez-Paz, Pascal Vincent
2024	J	`jnl`	Compositional Risk Minimization. CoRR Divyat Mahajan, Mohammad Pezeshki, Ioannis Mitliagkas, Kartik Ahuja, Pascal Vincent
2024	A*	`conf`	Discovering Environments with XRM. ICML Mohammad Pezeshki, Diane Bouchacourt, Mark Ibrahim, Nicolas Ballas, Pascal Vincent, David Lopez-Paz
2024	J	`jnl`	MaestroMotif: Skill Design from Artificial Intelligence Feedback. CoRR Martin Klissarov, Mikael Henaff, Roberta Raileanu, Shagun Sodhani, Pascal Vincent, Amy Zhang, Pierre-Luc Bacon, Doina Precup, Marlos C. Machado, Pierluca D'Oro
2024	A*	`conf`	Motif: Intrinsic Motivation from Artificial Intelligence Feedback. ICLR Martin Klissarov, Pierluca D'Oro, Shagun Sodhani, Roberta Raileanu, Pierre-Luc Bacon, Pascal Vincent, Amy Zhang, Mikael Henaff
2024	—	`conf`	On the Identifiability of Quantized Factors. CLeaR Vitória Barin Pacela, Kartik Ahuja, Simon Lacoste-Julien, Pascal Vincent
2024	A*	`conf`	Stochastic positional embeddings improve masked image modeling. ICML Amir Bar, Florian Bordes, Assaf Shocher, Mido Assran, Pascal Vincent, Nicolas Ballas, Trevor Darrell, Amir Globerson, Yann LeCun
2024	J	`jnl`	The Pitfalls of Memorization: When Memorization Hurts Generalization. CoRR Reza Bayat, Mohammad Pezeshki, Elvis Dohmatob, David Lopez-Paz, Pascal Vincent
2023	J	`jnl`	A surprisingly simple technique to control the pretraining bias for better transfer: Expand or Narrow your representation. CoRR Florian Bordes, Samuel Lavoie, Randall Balestriero, Nicolas Ballas, Pascal Vincent
2023	J	`jnl`	Discovering environments with XRM. CoRR Mohammad Pezeshki, Diane Bouchacourt, Mark Ibrahim, Nicolas Ballas, Pascal Vincent, David Lopez-Paz
2023	A*	`conf`	Disentanglement of Correlated Factors via Hausdorff Factorized Support. ICLR Karsten Roth, Mark Ibrahim, Zeynep Akata, Pascal Vincent, Diane Bouchacourt
2023	A*	`conf`	Do SSL Models Have Déjà Vu? A Case of Unintended Memorization in Self-supervised Learning. NeurIPS Casey Meehan, Florian Bordes, Pascal Vincent, Kamalika Chaudhuri, Chuan Guo
2023	J	`jnl`	Do SSL Models Have Déjà Vu? A Case of Unintended Memorization in Self-supervised Learning. CoRR Casey Meehan, Florian Bordes, Pascal Vincent, Kamalika Chaudhuri, Chuan Guo
2023	J	`jnl`	Guillotine Regularization: Why removing layers is needed to improve generalization in Self-Supervised Learning. Trans. Mach. Learn. Res. Florian Bordes, Randall Balestriero, Quentin Garrido, Adrien Bardes, Pascal Vincent
2023	J	`jnl`	Identifiability of Discretized Latent Coordinate Systems via Density Landmarks Detection. CoRR Vitória Barin Pacela, Kartik Ahuja, Simon Lacoste-Julien, Pascal Vincent
2023	A*	`conf`	ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations. ICLR Badr Youbi Idrissi, Diane Bouchacourt, Randall Balestriero, Ivan Evtimov, Caner Hazirbas, Nicolas Ballas, Pascal Vincent, Michal Drozdzal, David Lopez-Paz, Mark Ibrahim
2023	J	`jnl`	Instance-Conditioned GAN Data Augmentation for Representation Learning. CoRR Pietro Astolfi, Arantxa Casanova, Jakob Verbeek, Pascal Vincent, Adriana Romero-Soriano, Michal Drozdzal
2023	J	`jnl`	Motif: Intrinsic Motivation from Artificial Intelligence Feedback. CoRR Martin Klissarov, Pierluca D'Oro, Shagun Sodhani, Roberta Raileanu, Pierre-Luc Bacon, Pascal Vincent, Amy Zhang, Mikael Henaff
2023	J	`jnl`	Objectives Matter: Understanding the Impact of Self-Supervised Objectives on Vision Transformer Representations. CoRR Shashank Shekhar, Florian Bordes, Pascal Vincent, Ari Morcos
2023	A*	`conf`	PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning. NeurIPS Florian Bordes, Shashank Shekhar, Mark Ibrahim, Diane Bouchacourt, Pascal Vincent, Ari Morcos
2023	J	`jnl`	PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning. CoRR Florian Bordes, Shashank Shekhar, Mark Ibrahim, Diane Bouchacourt, Pascal Vincent, Ari S. Morcos
2023	J	`jnl`	Predicting masked tokens in stochastic locations improves masked image modeling. CoRR Amir Bar, Florian Bordes, Assaf Shocher, Mahmoud Assran, Pascal Vincent, Nicolas Ballas, Trevor Darrell, Amir Globerson, Yann LeCun
2023	J	`jnl`	Self-Supervised Disentanglement by Leveraging Structure in Data Augmentations. CoRR Cian Eastwood, Julius von Kügelgen, Linus Ericsson, Diane Bouchacourt, Pascal Vincent, Bernhard Schölkopf, Mark Ibrahim
2023	A*	`conf`	Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture. CVPR Mahmoud Assran, Quentin Duval, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Michael G. Rabbat, Yann LeCun, Nicolas Ballas
2023	J	`jnl`	Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture. CoRR Mahmoud Assran, Quentin Duval, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Michael G. Rabbat, Yann LeCun, Nicolas Ballas
2023	A*	`conf`	The hidden uniform cluster prior in self-supervised learning. ICLR Mido Assran, Randall Balestriero, Quentin Duval, Florian Bordes, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Michael G. Rabbat, Nicolas Ballas
2023	J	`jnl`	Towards Democratizing Joint-Embedding Self-Supervised Learning. CoRR Florian Bordes, Randall Balestriero, Pascal Vincent
2023	J	`jnl`	WorldSense: A Synthetic Benchmark for Grounded Reasoning in Large Language Models. CoRR Youssef Benchekroun, Megi Dervishi, Mark Ibrahim, Jean-Baptiste Gaya, Xavier Martinet, Grégoire Mialon, Thomas Scialom, Emmanuel Dupoux, Dieuwke Hupkes, Pascal Vincent
2022	J	`jnl`	Disentanglement of Correlated Factors via Hausdorff Factorized Support. CoRR Karsten Roth, Mark Ibrahim, Zeynep Akata, Pascal Vincent, Diane Bouchacourt
2022	J	`jnl`	Guillotine Regularization: Improving Deep Networks Generalization by Removing their Head. CoRR Florian Bordes, Randall Balestriero, Quentin Garrido, Adrien Bardes, Pascal Vincent
2022	J	`jnl`	High Fidelity Visualization of What Your Self-Supervised Representation Knows About. Trans. Mach. Learn. Res. Florian Bordes, Randall Balestriero, Pascal Vincent
2022	J	`jnl`	ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations. CoRR Badr Youbi Idrissi, Diane Bouchacourt, Randall Balestriero, Ivan Evtimov, Caner Hazirbas, Nicolas Ballas, Pascal Vincent, Michal Drozdzal, David Lopez-Paz, Mark Ibrahim
2022	—	`conf`	Masked Siamese Networks for Label-Efficient Learning. ECCV (31) Mahmoud Assran, Mathilde Caron, Ishan Misra, Piotr Bojanowski, Florian Bordes, Pascal Vincent, Armand Joulin, Mike Rabbat, Nicolas Ballas
2022	J	`jnl`	Masked Siamese Networks for Label-Efficient Learning. CoRR Mahmoud Assran, Mathilde Caron, Ishan Misra, Piotr Bojanowski, Florian Bordes, Pascal Vincent, Armand Joulin, Michael G. Rabbat, Nicolas Ballas
2022	A*	`conf`	Online Adversarial Attacks. ICLR Andjela Mladenovic, Avishek Joey Bose, Hugo Berard, William L. Hamilton, Simon Lacoste-Julien, Pascal Vincent, Gauthier Gidel
2022	J	`jnl`	The Emergence of Argument Structure in Artificial Languages. Trans. Assoc. Comput. Linguistics Tom Bosc, Pascal Vincent
2022	J	`jnl`	The Hidden Uniform Cluster Prior in Self-Supervised Learning. CoRR Mahmoud Assran, Randall Balestriero, Quentin Duval, Florian Bordes, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Michael G. Rabbat, Nicolas Ballas
2022	A*	`conf`	Understanding Dimensional Collapse in Contrastive Self-supervised Learning. ICLR Li Jing, Pascal Vincent, Yann LeCun, Yuandong Tian
2021	—	`conf`	Accounting for Variance in Machine Learning Benchmarks. MLSys 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
2021	J	`jnl`	Accounting for Variance in Machine Learning Benchmarks. CoRR 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
2021	J	`jnl`	High Fidelity Visualization of What Your Self-Supervised Representation Knows About. CoRR Florian Bordes, Randall Balestriero, Pascal Vincent
2021	A	`conf`	Implicit Regularization via Neural Feature Alignment. AISTATS Aristide Baratin, Thomas George, César Laurent, R. Devon Hjelm, Guillaume Lajoie, Pascal Vincent, Simon Lacoste-Julien
2021	J	`jnl`	Online Adversarial Attacks. CoRR Andjela Mladenovic, Avishek Joey Bose, Hugo Berard, William L. Hamilton, Simon Lacoste-Julien, Pascal Vincent, Gauthier Gidel
2021	J	`jnl`	Understanding Dimensional Collapse in Contrastive Self-supervised Learning. CoRR Li Jing, Pascal Vincent, Yann LeCun, Yuandong Tian
2020	A*	`conf`	A Closer Look at the Optimization Landscapes of Generative Adversarial Networks. ICLR Hugo Berard, Gauthier Gidel, Amjad Almahairi, Pascal Vincent, Simon Lacoste-Julien
2020	A*	`conf`	Adversarial Example Games. NeurIPS Avishek Joey Bose, Gauthier Gidel, Hugo Berard, Andre Cianflone, Pascal Vincent, Simon Lacoste-Julien, William L. Hamilton
2020	J	`jnl`	Adversarial Example Games. CoRR Avishek Joey Bose, Gauthier Gidel, Hugo Berard, Andre Cianflone, Pascal Vincent, Simon Lacoste-Julien, William L. Hamilton
2020	—	`conf`	Do sequence-to-sequence VAEs learn global features of sentences? EMNLP (1) Tom Bosc, Pascal Vincent
2020	J	`jnl`	Do sequence-to-sequence VAEs learn global features of sentences? CoRR Tom Bosc, Pascal Vincent
2020	J	`jnl`	Efficient Learning in Non-Stationary Linear Markov Decision Processes. CoRR Ahmed Touati, Pascal Vincent
2020	J	`jnl`	Implicit Regularization in Deep Learning: A View from Function Space. CoRR Aristide Baratin, Thomas George, César Laurent, R. Devon Hjelm, Guillaume Lajoie, Pascal Vincent, Simon Lacoste-Julien
2020	J	`jnl`	Revisiting Loss Modelling for Unstructured Pruning. CoRR César Laurent, Camille Ballas, Thomas George, Nicolas Ballas, Pascal Vincent
2020	A*	`conf`	SVRG for Policy Evaluation with Fewer Gradient Evaluations. IJCAI Zilun Peng, Ahmed Touati, Pascal Vincent, Doina Precup
2020	J	`jnl`	Sharp Analysis of Smoothed Bellman Error Embedding. CoRR Ahmed Touati, Pascal Vincent
2020	A	`conf`	Stable Policy Optimization via Off-Policy Divergence Regularization. UAI Ahmed Touati, Amy Zhang, Joelle Pineau, Pascal Vincent
2020	J	`jnl`	Stable Policy Optimization via Off-Policy Divergence Regularization. CoRR Ahmed Touati, Amy Zhang, Joelle Pineau, Pascal Vincent
2020	A*	`conf`	Stochastic Hamiltonian Gradient Methods for Smooth Games. ICML Nicolas Loizou, Hugo Berard, Alexia Jolicoeur-Martineau, Pascal Vincent, Simon Lacoste-Julien, Ioannis Mitliagkas
2020	J	`jnl`	Stochastic Hamiltonian Gradient Methods for Smooth Games. CoRR Nicolas Loizou, Hugo Berard, Alexia Jolicoeur-Martineau, Pascal Vincent, Simon Lacoste-Julien, Ioannis Mitliagkas
2020	A	`conf`	Stochastic Neural Network with Kronecker Flow. AISTATS Chin-Wei Huang, Ahmed Touati, Pascal Vincent, Gintare Karolina Dziugaite, Alexandre Lacoste, Aaron C. Courville
2019	J	`jnl`	A Closer Look at the Optimization Landscapes of Generative Adversarial Networks. CoRR Hugo Berard, Gauthier Gidel, Amjad Almahairi, Pascal Vincent, Simon Lacoste-Julien
2019	—	`conf`	A Variational Inequality Perspective on Generative Adversarial Networks. ICLR (Poster) Gauthier Gidel, Hugo Berard, Gaëtan Vignoud, Pascal Vincent, Simon Lacoste-Julien
2019	J	`jnl`	An Empirical Study of Batch Normalization and Group Normalization in Conditional Computation. CoRR Vincent Michalski, Vikram Voleti, Samira Ebrahimi Kahou, Anthony Ortiz, Pascal Vincent, Chris Pal, Doina Precup
2019	A	`conf`	Randomized Value Functions via Multiplicative Normalizing Flows. UAI Ahmed Touati, Harsh Satija, Joshua Romoff, Joelle Pineau, Pascal Vincent
2019	A*	`conf`	Reducing Uncertainty in Undersampled MRI Reconstruction With Active Acquisition. CVPR Zizhao Zhang, Adriana Romero, Matthew J. Muckley, Pascal Vincent, Lin Yang, Michal Drozdzal
2019	J	`jnl`	Reducing Uncertainty in Undersampled MRI Reconstruction with Active Acquisition. CoRR Zizhao Zhang, Adriana Romero, Matthew J. Muckley, Pascal Vincent, Lin Yang, Michal Drozdzal
2019	J	`jnl`	SVRG for Policy Evaluation with Fewer Gradient Evaluations. CoRR Zilun Peng, Ahmed Touati, Pascal Vincent, Doina Precup
2019	J	`jnl`	Stochastic Neural Network with Kronecker Flow. CoRR Chin-Wei Huang, Ahmed Touati, Pascal Vincent, Gintare Karolina Dziugaite, Alexandre Lacoste, Aaron C. Courville
2019	A*	`conf`	Unreproducible Research is Reproducible. ICML Xavier Bouthillier, César Laurent, Pascal Vincent
2018	J	`jnl`	A Variational Inequality Perspective on Generative Adversarial Nets. CoRR Gauthier Gidel, Hugo Berard, Pascal Vincent, Simon Lacoste-Julien
2018	—	`conf`	An Evaluation of Fisher Approximations Beyond Kronecker Factorization. ICLR (Workshop) César Laurent, Thomas George, Xavier Bouthillier, Nicolas Ballas, Pascal Vincent
2018	A*	`conf`	Auto-Encoding Dictionary Definitions into Consistent Word Embeddings. EMNLP Tom Bosc, Pascal Vincent
2018	A*	`conf`	Convergent TREE BACKUP and RETRACE with Function Approximation. ICML Ahmed Touati, Pierre-Luc Bacon, Doina Precup, Pascal Vincent
2018	A*	`conf`	Fast Approximate Natural Gradient Descent in a Kronecker Factored Eigenbasis. NeurIPS Thomas George, César Laurent, Xavier Bouthillier, Nicolas Ballas, Pascal Vincent
2018	J	`jnl`	Fast Approximate Natural Gradient Descent in a Kronecker-factored Eigenbasis. CoRR Thomas George, César Laurent, Xavier Bouthillier, Nicolas Ballas, Pascal Vincent
2018	A*	`conf`	Improving Landmark Localization With Semi-Supervised Learning. CVPR Sina Honari, Pavlo Molchanov, Stephen Tyree, Pascal Vincent, Christopher J. Pal, Jan Kautz
2018	—	`conf`	Parametric Adversarial Divergences are Good Task Losses for Generative Modeling. ICLR (Workshop) Gabriel Huang, Hugo Berard, Ahmed Touati, Gauthier Gidel, Pascal Vincent, Simon Lacoste-Julien
2018	J	`jnl`	Randomized Value Functions via Multiplicative Normalizing Flows. CoRR Ahmed Touati, Harsh Satija, Joshua Romoff, Joelle Pineau, Pascal Vincent
2018	J	`jnl`	fastMRI: An Open Dataset and Benchmarks for Accelerated MRI. CoRR 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
2017	J	`jnl`	Convergent Tree-Backup and Retrace with Function Approximation. CoRR Ahmed Touati, Pierre-Luc Bacon, Doina Precup, Pascal Vincent
2017	J	`jnl`	Improving Landmark Localization with Semi-Supervised Learning. CoRR Sina Honari, Pavlo Molchanov, Stephen Tyree, Pascal Vincent, Christopher Joseph Pal, Jan Kautz
2017	J	`jnl`	Learning to Compute Word Embeddings On the Fly. CoRR Dzmitry Bahdanau, Tom Bosc, Stanislaw Jastrzebski, Edward Grefenstette, Pascal Vincent, Yoshua Bengio
2017	—	`conf`	Learning to Generate Samples from Noise through Infusion Training. ICLR (Poster) Florian Bordes, Sina Honari, Pascal Vincent
2017	J	`jnl`	Learning to Generate Samples from Noise through Infusion Training. CoRR Florian Bordes, Sina Honari, Pascal Vincent
2017	—	`conf`	RATM: Recurrent Attentive Tracking Model. CVPR Workshops Samira Ebrahimi Kahou, Vincent Michalski, Roland Memisevic, Christopher Joseph Pal, Pascal Vincent
2017	—	`conf`	Recurrent Normalization Propagation. ICLR (Workshop) César Laurent, Nicolas Ballas, Pascal Vincent
2016	J	`jnl`	A Cheap Linear Attention Mechanism with Fast Lookups and Fixed-Size Representations. CoRR Alexandre de Brébisson, Pascal Vincent
2016	A*	`conf`	An Exploration of Softmax Alternatives Belonging to the Spherical Loss Family. ICLR (Poster) Alexandre de Brébisson, Pascal Vincent
2016	J	`jnl`	EmoNets: Multimodal deep learning approaches for emotion recognition in video. J. Multimodal User Interfaces 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
2016	J	`jnl`	Exact gradient updates in time independent of output size for the spherical loss family. CoRR Pascal Vincent, Alexandre de Brébisson, Xavier Bouthillier
2016	J	`jnl`	Hierarchical Memory Networks. CoRR Sarath Chandar, Sungjin Ahn, Hugo Larochelle, Pascal Vincent, Gerald Tesauro, Yoshua Bengio
2016	A*	`conf`	Recombinator Networks: Learning Coarse-to-Fine Feature Aggregation. CVPR Sina Honari, Jason Yosinski, Pascal Vincent, Christopher J. Pal
2016	J	`jnl`	The Z-loss: a shift and scale invariant classification loss belonging to the Spherical Family. CoRR Alexandre de Brébisson, Pascal Vincent
2016	J	`jnl`	Theano: A Python framework for fast computation of mathematical expressions. CoRR 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
2015	—	`conf`	Artificial Neural Networks Applied to Taxi Destination Prediction. DC@PKDD/ECML Alexandre de Brébisson, Étienne Simon, Alex Auvolat, Pascal Vincent, Yoshua Bengio
2015	J	`jnl`	Artificial Neural Networks Applied to Taxi Destination Prediction. CoRR Alexandre de Brébisson, Étienne Simon, Alex Auvolat, Pascal Vincent, Yoshua Bengio
2015	J	`jnl`	Clustering is Efficient for Approximate Maximum Inner Product Search. CoRR Alex Auvolat, Pascal Vincent
2015	J	`jnl`	Dropout as data augmentation. CoRR Kishore Reddy Konda, Xavier Bouthillier, Roland Memisevic, Pascal Vincent
2015	—	`conf`	Efficient Exact Gradient Update for training Deep Networks with Very Large Sparse Targets. NIPS Pascal Vincent, Alexandre de Brébisson, Xavier Bouthillier
2015	—	`conf`	Efficient Exact Gradient Update for training Deep Networks with Very Large Sparse Targets. ICLR (Workshop) Pascal Vincent
2015	J	`jnl`	EmoNets: Multimodal deep learning approaches for emotion recognition in video. CoRR Samira Ebrahimi Kahou, Xavier Bouthillier, Pascal Lamblin, Çaglar Gülçehre, Vincent Michalski, Kishore Reddy 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 J. Pal, Yoshua Bengio
2015	J	`jnl`	GSNs : Generative Stochastic Networks. CoRR Guillaume Alain, Yoshua Bengio, Li Yao, Jason Yosinski, Eric Thibodeau-Laufer, Saizheng Zhang, Pascal Vincent
2015	J	`jnl`	Recombinator Networks: Learning Coarse-to-Fine Feature Aggregation. CoRR Sina Honari, Jason Yosinski, Pascal Vincent, Christopher J. Pal
2013	—	`conf`	Audio Chord Recognition with Recurrent Neural Networks. ISMIR Nicolas Boulanger-Lewandowski, Yoshua Bengio, Pascal Vincent
2013	B	`conf`	Combining modality specific deep neural networks for emotion recognition in video. ICMI 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
2013	J	`jnl`	Generalized Denoising Auto-Encoders as Generative Models CoRR Yoshua Bengio, Li Yao, Guillaume Alain, Pascal Vincent
2013	—	`conf`	Generalized Denoising Auto-Encoders as Generative Models. NIPS Yoshua Bengio, Li Yao, Guillaume Alain, Pascal Vincent
2013	Misc	`conf`	High-dimensional sequence transduction. ICASSP Nicolas Boulanger-Lewandowski, Yoshua Bengio, Pascal Vincent
2013	J	`jnl`	Representation Learning: A Review and New Perspectives. IEEE Trans. Pattern Anal. Mach. Intell. Yoshua Bengio, Aaron C. Courville, Pascal Vincent
2013	—	`conf`	Semi Supervised Autoencoders: Better Focusing Model Capacity during Feature Extraction. ICONIP (1) Hani Almousli, Pascal Vincent
2013	—	`conf`	Unsupervised Learning of Semantics of Object Detections for Scene Categorization. ICPRAM (Selected Papers) Grégoire Mesnil, Salah Rifai, Antoine Bordes, Xavier Glorot, Yoshua Bengio, Pascal Vincent
2013	C	`conf`	Unsupervised and Transfer Learning under Uncertainty - From Object Detections to Scene Categorization. ICPRAM Grégoire Mesnil, Salah Rifai, Antoine Bordes, Xavier Glorot, Yoshua Bengio, Pascal Vincent
2012	A*	`conf`	A Generative Process for Contractive Auto-Encoders. ICML Salah Rifai, Yann N. Dauphin, Pascal Vincent, Yoshua Bengio
2012	—	`conf`	Discriminative Non-negative Matrix Factorization for Multiple Pitch Estimation. ISMIR Nicolas Boulanger-Lewandowski, Yoshua Bengio, Pascal Vincent
2012	—	`conf`	Disentangling Factors of Variation for Facial Expression Recognition. ECCV (6) Salah Rifai, Yoshua Bengio, Aaron C. Courville, Pascal Vincent, Mehdi Mirza
2012	J	`jnl`	High-dimensional sequence transduction CoRR Nicolas Boulanger-Lewandowski, Yoshua Bengio, Pascal Vincent
2012	A*	`conf`	Modeling Temporal Dependencies in High-Dimensional Sequences: Application to Polyphonic Music Generation and Transcription. ICML Nicolas Boulanger-Lewandowski, Yoshua Bengio, Pascal Vincent
2012	J	`jnl`	Unsupervised Feature Learning and Deep Learning: A Review and New Perspectives CoRR Yoshua Bengio, Aaron C. Courville, Pascal Vincent
2012	—	`conf`	Unsupervised and Transfer Learning Challenge: a Deep Learning Approach. ICML Unsupervised and Transfer Learning 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
2011	J	`jnl`	A Connection Between Score Matching and Denoising Autoencoders. Neural Comput. Pascal Vincent
2011	J	`jnl`	A high-order feature synthesis and selection algorithm applied to insurance risk modelling. Int. J. Bus. Intell. Data Min. Charles Dugas, Nicolas Chapados, Réjean Ducharme, Xavier Saint-Mleux, Pascal Vincent
2011	J	`jnl`	Adding noise to the input of a model trained with a regularized objective CoRR Salah Rifai, Xavier Glorot, Yoshua Bengio, Pascal Vincent
2011	A*	`conf`	Contractive Auto-Encoders: Explicit Invariance During Feature Extraction. ICML Salah Rifai, Pascal Vincent, Xavier Muller, Xavier Glorot, Yoshua Bengio
2011	—	`conf`	Fabrication and characterization of 100-nm wide silicon nanocantilevers using top-down approach. NEMS Samuel Guillon, Daisuke Saya, Laurent Mazenq, Liviu Nicu, Sorin Perisanu, Pascal Vincent
2011	—	`conf`	Higher Order Contractive Auto-Encoder. ECML/PKDD (2) Salah Rifai, Grégoire Mesnil, Pascal Vincent, Xavier Muller, Yoshua Bengio, Yann N. Dauphin, Xavier Glorot
2011	J	`jnl`	Learning invariant features through local space contraction CoRR Salah Rifai, Xavier Muller, Xavier Glorot, Grégoire Mesnil, Yoshua Bengio, Pascal Vincent
2011	J	`jnl`	Quickly Generating Representative Samples from an RBM-Derived Process. Neural Comput. Olivier Breuleux, Yoshua Bengio, Pascal Vincent
2011	—	`conf`	The Manifold Tangent Classifier. NIPS Salah Rifai, Yann N. Dauphin, Pascal Vincent, Yoshua Bengio, Xavier Muller
2010	J	`jnl`	Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion. J. Mach. Learn. Res. Pascal Vincent, Hugo Larochelle, Isabelle Lajoie, Yoshua Bengio, Pierre-Antoine Manzagol
2010	A	`conf`	Tempered Markov Chain Monte Carlo for training of Restricted Boltzmann Machines. AISTATS Guillaume Desjardins, Aaron C. Courville, Yoshua Bengio, Pascal Vincent, Olivier Delalleau
2010	J	`jnl`	Why Does Unsupervised Pre-training Help Deep Learning? J. Mach. Learn. Res. Dumitru Erhan, Yoshua Bengio, Aaron C. Courville, Pierre-Antoine Manzagol, Pascal Vincent, Samy Bengio
2010	A	`conf`	Why Does Unsupervised Pre-training Help Deep Learning? AISTATS Dumitru Erhan, Aaron C. Courville, Yoshua Bengio, Pascal Vincent
2009	A	`conf`	Deep Learning using Robust Interdependent Codes. AISTATS Hugo Larochelle, Dumitru Erhan, Pascal Vincent
2009	A	`conf`	The Difficulty of Training Deep Architectures and the Effect of Unsupervised Pre-Training. AISTATS Dumitru Erhan, Pierre-Antoine Manzagol, Yoshua Bengio, Samy Bengio, Pascal Vincent
2008	A*	`conf`	Extracting and composing robust features with denoising autoencoders. ICML Pascal Vincent, Hugo Larochelle, Yoshua Bengio, Pierre-Antoine Manzagol
2008	—	`conf`	Scoring Models for Insurance Risk Sharing Pool Opimization. ICDM Workshops Nicolas Chapados, Charles Dugas, Pascal Vincent, Réjean Ducharme
2007	J	`jnl`	The Need for Open Source Software in Machine Learning. J. Mach. Learn. Res. 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
2006	—	`ch.`	Spectral Dimensionality Reduction. Feature Extraction Yoshua Bengio, Olivier Delalleau, Nicolas Le Roux, Jean-François Paiement, Pascal Vincent, Marie Ouimet
2005	—	`conf`	Convex Neural Networks. NIPS Yoshua Bengio, Nicolas Le Roux, Pascal Vincent, Olivier Delalleau, Patrice Marcotte
2005	—	`conf`	Non-Local Manifold Parzen Windows. NIPS Yoshua Bengio, Hugo Larochelle, Pascal Vincent
2004	J	`jnl`	Learning Eigenfunctions Links Spectral Embedding and Kernel PCA. Neural Comput. Yoshua Bengio, Olivier Delalleau, Nicolas Le Roux, Jean-François Paiement, Pascal Vincent, Marie Ouimet
2003	J	`jnl`	A Neural Probabilistic Language Model. J. Mach. Learn. Res. Yoshua Bengio, Réjean Ducharme, Pascal Vincent, Christian Janvin
2003	—	`conf`	Out-of-Sample Extensions for LLE, Isomap, MDS, Eigenmaps, and Spectral Clustering. NIPS Yoshua Bengio, Jean-François Paiement, Pascal Vincent, Olivier Delalleau, Nicolas Le Roux, Marie Ouimet
2002	J	`jnl`	Kernel Matching Pursuit. Mach. Learn. Pascal Vincent, Yoshua Bengio
2002	—	`conf`	Manifold Parzen Windows. NIPS Pascal Vincent, Yoshua Bengio
2001	—	`conf`	Estimating Car Insurance Premia: a Case Study in High-Dimensional Data Inference. NIPS Nicolas Chapados, Yoshua Bengio, Pascal Vincent, Joumana Ghosn, Charles Dugas, Ichiro Takeuchi, Linyan Meng
2001	—	`conf`	K-Local Hyperplane and Convex Distance Nearest Neighbor Algorithms. NIPS Pascal Vincent, Yoshua Bengio
2001	C	`conf`	ROBOSIX UPMC-CFA: RoboCup Team Description. RoboCup 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
2000	—	`conf`	A Neural Probabilistic Language Model. NIPS Yoshua Bengio, Réjean Ducharme, Pascal Vincent
2000	—	`conf`	A Neural Support Vector Network Architecture with Adaptive Kernels. IJCNN (5) Pascal Vincent, Yoshua Bengio
1999	—	`conf`	Color Documents on the Web with DJVU. ICIP (1) Patrick Haffner, Yann LeCun, Léon Bottou, Paul G. Howard, Pascal Vincent, Bill Riemers
1990	Misc	`conf`	Region Tracking through Neural Classifier. MVA Patrick Thévenoux, Pascal Vincent