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- affiliation: University of Montreal, Canada
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2020 – today
- 2024
[c73]Vitória Barin Pacela, Kartik Ahuja, Simon Lacoste-Julien, Pascal Vincent:
On the Identifiability of Quantized Factors. CLeaR 2024: 384-422- [c72]Martin Klissarov, Pierluca D'Oro, Shagun Sodhani, Roberta Raileanu, Pierre-Luc Bacon, Pascal Vincent, Amy Zhang, Mikael Henaff:
Motif: Intrinsic Motivation from Artificial Intelligence Feedback. ICLR 2024 - [c71]Amir Bar, Florian Bordes, Assaf Shocher, Mido Assran, Pascal Vincent, Nicolas Ballas, Trevor Darrell, Amir Globerson, Yann LeCun:
Stochastic positional embeddings improve masked image modeling. ICML 2024 - [c70]Mohammad Pezeshki, Diane Bouchacourt, Mark Ibrahim, Nicolas Ballas, Pascal Vincent, David Lopez-Paz:
Discovering Environments with XRM. ICML 2024 - [i60]Divyat Mahajan, Mohammad Pezeshki, Ioannis Mitliagkas, Kartik Ahuja, Pascal Vincent:
Compositional Risk Minimization. CoRR abs/2410.06303 (2024) - 2023
- [j14]Florian Bordes, Randall Balestriero, Quentin Garrido, Adrien Bardes, Pascal Vincent:
Guillotine Regularization: Why removing layers is needed to improve generalization in Self-Supervised Learning. Trans. Mach. Learn. Res. 2023 (2023) - [c69]Mahmoud Assran, Quentin Duval, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Michael G. Rabbat, Yann LeCun, Nicolas Ballas:
Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture. CVPR 2023: 15619-15629 - [c68]Mido Assran, Randall Balestriero, Quentin Duval, Florian Bordes, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Michael G. Rabbat, Nicolas Ballas:
The hidden uniform cluster prior in self-supervised learning. ICLR 2023 - [c67]Badr Youbi Idrissi, Diane Bouchacourt, Randall Balestriero, Ivan Evtimov, Caner Hazirbas, Nicolas Ballas, Pascal Vincent, Michal Drozdzal, David Lopez-Paz, Mark Ibrahim:
ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations. ICLR 2023 - [c66]Karsten Roth, Mark Ibrahim, Zeynep Akata, Pascal Vincent, Diane Bouchacourt:
Disentanglement of Correlated Factors via Hausdorff Factorized Support. ICLR 2023 - [c65]Florian Bordes, Shashank Shekhar, Mark Ibrahim, Diane Bouchacourt, Pascal Vincent, Ari Morcos:
PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning. NeurIPS 2023 - [c64]Casey Meehan, Florian Bordes, Pascal Vincent, Kamalika Chaudhuri, Chuan Guo:
Do SSL Models Have Déjà Vu? A Case of Unintended Memorization in Self-supervised Learning. NeurIPS 2023 - [i59]Mahmoud Assran, Quentin Duval, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Michael G. Rabbat, Yann LeCun, Nicolas Ballas:
Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture. CoRR abs/2301.08243 (2023) - [i58]Florian Bordes, Randall Balestriero, Pascal Vincent:
Towards Democratizing Joint-Embedding Self-Supervised Learning. CoRR abs/2303.01986 (2023) - [i57]Pietro Astolfi, Arantxa Casanova, Jakob Verbeek, Pascal Vincent, Adriana Romero-Soriano, Michal Drozdzal:
Instance-Conditioned GAN Data Augmentation for Representation Learning. CoRR abs/2303.09677 (2023) - [i56]Florian Bordes, Samuel Lavoie, Randall Balestriero, Nicolas Ballas, Pascal Vincent:
A surprisingly simple technique to control the pretraining bias for better transfer: Expand or Narrow your representation. CoRR abs/2304.05369 (2023) - [i55]Shashank Shekhar, Florian Bordes, Pascal Vincent, Ari Morcos:
Objectives Matter: Understanding the Impact of Self-Supervised Objectives on Vision Transformer Representations. CoRR abs/2304.13089 (2023) - [i54]Casey Meehan, Florian Bordes, Pascal Vincent, Kamalika Chaudhuri, Chuan Guo:
Do SSL Models Have Déjà Vu? A Case of Unintended Memorization in Self-supervised Learning. CoRR abs/2304.13850 (2023) - [i53]Vitória Barin Pacela, Kartik Ahuja, Simon Lacoste-Julien, Pascal Vincent:
Identifiability of Discretized Latent Coordinate Systems via Density Landmarks Detection. CoRR abs/2306.16334 (2023) - [i52]Amir Bar, Florian Bordes, Assaf Shocher, Mahmoud Assran, Pascal Vincent, Nicolas Ballas, Trevor Darrell, Amir Globerson, Yann LeCun:
Predicting masked tokens in stochastic locations improves masked image modeling. CoRR abs/2308.00566 (2023) - [i51]Florian Bordes, Shashank Shekhar, Mark Ibrahim, Diane Bouchacourt, Pascal Vincent, Ari S. Morcos:
PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning. CoRR abs/2308.03977 (2023) - [i50]Mohammad Pezeshki, Diane Bouchacourt, Mark Ibrahim, Nicolas Ballas, Pascal Vincent, David Lopez-Paz:
Discovering environments with XRM. CoRR abs/2309.16748 (2023) - [i49]Martin Klissarov, Pierluca D'Oro, Shagun Sodhani, Roberta Raileanu, Pierre-Luc Bacon, Pascal Vincent, Amy Zhang, Mikael Henaff:
Motif: Intrinsic Motivation from Artificial Intelligence Feedback. CoRR abs/2310.00166 (2023) - [i48]Cian Eastwood, Julius von Kügelgen, Linus Ericsson, Diane Bouchacourt, Pascal Vincent, Bernhard Schölkopf, Mark Ibrahim:
Self-Supervised Disentanglement by Leveraging Structure in Data Augmentations. CoRR abs/2311.08815 (2023) - [i47]Youssef Benchekroun, Megi Dervishi, Mark Ibrahim, Jean-Baptiste Gaya, Xavier Martinet, Grégoire Mialon, Thomas Scialom, Emmanuel Dupoux, Dieuwke Hupkes, Pascal Vincent:
WorldSense: A Synthetic Benchmark for Grounded Reasoning in Large Language Models. CoRR abs/2311.15930 (2023) - 2022
- [j13]Tom Bosc, Pascal Vincent:
The Emergence of Argument Structure in Artificial Languages. Trans. Assoc. Comput. Linguistics 10: 1375-1391 (2022) - [j12]Florian Bordes, Randall Balestriero, Pascal Vincent:
High Fidelity Visualization of What Your Self-Supervised Representation Knows About. Trans. Mach. Learn. Res. 2022 (2022) - [c63]Mahmoud Assran, Mathilde Caron, Ishan Misra, Piotr Bojanowski, Florian Bordes, Pascal Vincent, Armand Joulin, Mike Rabbat, Nicolas Ballas:
Masked Siamese Networks for Label-Efficient Learning. ECCV (31) 2022: 456-473 - [c62]Li Jing, Pascal Vincent, Yann LeCun, Yuandong Tian:
Understanding Dimensional Collapse in Contrastive Self-supervised Learning. ICLR 2022 - [c61]Andjela Mladenovic, Avishek Joey Bose, Hugo Berard, William L. Hamilton, Simon Lacoste-Julien, Pascal Vincent, Gauthier Gidel:
Online Adversarial Attacks. ICLR 2022 - [i46]Mahmoud Assran, Mathilde Caron, Ishan Misra, Piotr Bojanowski, Florian Bordes, Pascal Vincent, Armand Joulin, Michael G. Rabbat, Nicolas Ballas:
Masked Siamese Networks for Label-Efficient Learning. CoRR abs/2204.07141 (2022) - [i45]Florian Bordes, Randall Balestriero, Quentin Garrido, Adrien Bardes, Pascal Vincent:
Guillotine Regularization: Improving Deep Networks Generalization by Removing their Head. CoRR abs/2206.13378 (2022) - [i44]Mahmoud Assran, Randall Balestriero, Quentin Duval, Florian Bordes, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Michael G. Rabbat, Nicolas Ballas:
The Hidden Uniform Cluster Prior in Self-Supervised Learning. CoRR abs/2210.07277 (2022) - [i43]Karsten Roth, Mark Ibrahim, Zeynep Akata, Pascal Vincent, Diane Bouchacourt:
Disentanglement of Correlated Factors via Hausdorff Factorized Support. CoRR abs/2210.07347 (2022) - [i42]Badr Youbi Idrissi, Diane Bouchacourt, Randall Balestriero, Ivan Evtimov, Caner Hazirbas, Nicolas Ballas, Pascal Vincent, Michal Drozdzal, David Lopez-Paz, Mark Ibrahim:
ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations. CoRR abs/2211.01866 (2022) - 2021
- [c60]Aristide Baratin, Thomas George, César Laurent, R. Devon Hjelm, Guillaume Lajoie, Pascal Vincent, Simon Lacoste-Julien:
Implicit Regularization via Neural Feature Alignment. AISTATS 2021: 2269-2277 - [c59]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:
Accounting for Variance in Machine Learning Benchmarks. MLSys 2021 - [i41]Andjela Mladenovic, Avishek Joey Bose, Hugo Berard, William L. Hamilton, Simon Lacoste-Julien, Pascal Vincent, Gauthier Gidel:
Online Adversarial Attacks. CoRR abs/2103.02014 (2021) - [i40]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:
Accounting for Variance in Machine Learning Benchmarks. CoRR abs/2103.03098 (2021) - [i39]Li Jing, Pascal Vincent, Yann LeCun, Yuandong Tian:
Understanding Dimensional Collapse in Contrastive Self-supervised Learning. CoRR abs/2110.09348 (2021) - [i38]Florian Bordes, Randall Balestriero, Pascal Vincent:
High Fidelity Visualization of What Your Self-Supervised Representation Knows About. CoRR abs/2112.09164 (2021) - 2020
- [c58]Chin-Wei Huang, Ahmed Touati, Pascal Vincent, Gintare Karolina Dziugaite, Alexandre Lacoste, Aaron C. Courville:
Stochastic Neural Network with Kronecker Flow. AISTATS 2020: 4184-4194 - [c57]Tom Bosc, Pascal Vincent:
Do sequence-to-sequence VAEs learn global features of sentences? EMNLP (1) 2020: 4296-4318 - [c56]Hugo Berard, Gauthier Gidel, Amjad Almahairi, Pascal Vincent, Simon Lacoste-Julien:
A Closer Look at the Optimization Landscapes of Generative Adversarial Networks. ICLR 2020 - [c55]Nicolas Loizou, Hugo Berard, Alexia Jolicoeur-Martineau, Pascal Vincent, Simon Lacoste-Julien, Ioannis Mitliagkas:
Stochastic Hamiltonian Gradient Methods for Smooth Games. ICML 2020: 6370-6381 - [c54]Zilun Peng, Ahmed Touati, Pascal Vincent, Doina Precup:
SVRG for Policy Evaluation with Fewer Gradient Evaluations. IJCAI 2020: 2697-2703 - [c53]Avishek Joey Bose, Gauthier Gidel, Hugo Berard, Andre Cianflone, Pascal Vincent, Simon Lacoste-Julien, William L. Hamilton:
Adversarial Example Games. NeurIPS 2020 - [c52]Ahmed Touati, Amy Zhang, Joelle Pineau, Pascal Vincent:
Stable Policy Optimization via Off-Policy Divergence Regularization. UAI 2020: 1328-1337 - [i37]Ahmed Touati, Amy Zhang
, Joelle Pineau, Pascal Vincent:
Stable Policy Optimization via Off-Policy Divergence Regularization. CoRR abs/2003.04108 (2020) - [i36]Tom Bosc, Pascal Vincent:
Do sequence-to-sequence VAEs learn global features of sentences? CoRR abs/2004.07683 (2020) - [i35]César Laurent, Camille Ballas, Thomas George, Nicolas Ballas, Pascal Vincent:
Revisiting Loss Modelling for Unstructured Pruning. CoRR abs/2006.12279 (2020) - [i34]Avishek Joey Bose, Gauthier Gidel, Hugo Berard, Andre Cianflone, Pascal Vincent, Simon Lacoste-Julien, William L. Hamilton:
Adversarial Example Games. CoRR abs/2007.00720 (2020) - [i33]Ahmed Touati, Pascal Vincent:
Sharp Analysis of Smoothed Bellman Error Embedding. CoRR abs/2007.03749 (2020) - [i32]Nicolas Loizou, Hugo Berard, Alexia Jolicoeur-Martineau, Pascal Vincent, Simon Lacoste-Julien, Ioannis Mitliagkas:
Stochastic Hamiltonian Gradient Methods for Smooth Games. CoRR abs/2007.04202 (2020) - [i31]Aristide Baratin, Thomas George, César Laurent, R. Devon Hjelm, Guillaume Lajoie, Pascal Vincent, Simon Lacoste-Julien:
Implicit Regularization in Deep Learning: A View from Function Space. CoRR abs/2008.00938 (2020) - [i30]Ahmed Touati, Pascal Vincent:
Efficient Learning in Non-Stationary Linear Markov Decision Processes. CoRR abs/2010.12870 (2020)
2010 – 2019
- 2019
- [c51]Zizhao Zhang, Adriana Romero, Matthew J. Muckley, Pascal Vincent, Lin Yang, Michal Drozdzal:
Reducing Uncertainty in Undersampled MRI Reconstruction With Active Acquisition. CVPR 2019: 2049-2058 - [c50]Gauthier Gidel, Hugo Berard, Gaëtan Vignoud, Pascal Vincent, Simon Lacoste-Julien:
A Variational Inequality Perspective on Generative Adversarial Networks. ICLR (Poster) 2019 - [c49]Xavier Bouthillier, César Laurent, Pascal Vincent:
Unreproducible Research is Reproducible. ICML 2019: 725-734 - [c48]Ahmed Touati, Harsh Satija, Joshua Romoff, Joelle Pineau, Pascal Vincent:
Randomized Value Functions via Multiplicative Normalizing Flows. UAI 2019: 422-432 - [i29]Zizhao Zhang, Adriana Romero, Matthew J. Muckley, Pascal Vincent, Lin Yang, Michal Drozdzal:
Reducing Uncertainty in Undersampled MRI Reconstruction with Active Acquisition. CoRR abs/1902.03051 (2019) - [i28]Zilun Peng, Ahmed Touati, Pascal Vincent, Doina Precup:
SVRG for Policy Evaluation with Fewer Gradient Evaluations. CoRR abs/1906.03704 (2019) - [i27]Chin-Wei Huang, Ahmed Touati, Pascal Vincent, Gintare Karolina Dziugaite, Alexandre Lacoste, Aaron C. Courville:
Stochastic Neural Network with Kronecker Flow. CoRR abs/1906.04282 (2019) - [i26]Hugo Berard, Gauthier Gidel, Amjad Almahairi, Pascal Vincent, Simon Lacoste-Julien:
A Closer Look at the Optimization Landscapes of Generative Adversarial Networks. CoRR abs/1906.04848 (2019) - [i25]Vincent Michalski, Vikram Voleti, Samira Ebrahimi Kahou, Anthony Ortiz, Pascal Vincent, Chris Pal, Doina Precup:
An Empirical Study of Batch Normalization and Group Normalization in Conditional Computation. CoRR abs/1908.00061 (2019) - 2018
- [c47]Sina Honari, Pavlo Molchanov, Stephen Tyree, Pascal Vincent, Christopher J. Pal, Jan Kautz:
Improving Landmark Localization With Semi-Supervised Learning. CVPR 2018: 1546-1555 - [c46]Tom Bosc, Pascal Vincent:
Auto-Encoding Dictionary Definitions into Consistent Word Embeddings. EMNLP 2018: 1522-1532 - [c45]Gabriel Huang, Hugo Berard, Ahmed Touati, Gauthier Gidel, Pascal Vincent, Simon Lacoste-Julien:
Parametric Adversarial Divergences are Good Task Losses for Generative Modeling. ICLR (Workshop) 2018 - [c44]César Laurent, Thomas George, Xavier Bouthillier, Nicolas Ballas, Pascal Vincent:
An Evaluation of Fisher Approximations Beyond Kronecker Factorization. ICLR (Workshop) 2018 - [c43]Ahmed Touati, Pierre-Luc Bacon, Doina Precup, Pascal Vincent:
Convergent TREE BACKUP and RETRACE with Function Approximation. ICML 2018: 4962-4971 - [c42]Thomas George, César Laurent, Xavier Bouthillier, Nicolas Ballas, Pascal Vincent:
Fast Approximate Natural Gradient Descent in a Kronecker Factored Eigenbasis. NeurIPS 2018: 9573-9583 - [i24]Gauthier Gidel, Hugo Berard, Pascal Vincent, Simon Lacoste-Julien:
A Variational Inequality Perspective on Generative Adversarial Nets. CoRR abs/1802.10551 (2018) - [i23]Ahmed Touati, Harsh Satija, Joshua Romoff, Joelle Pineau, Pascal Vincent:
Randomized Value Functions via Multiplicative Normalizing Flows. CoRR abs/1806.02315 (2018) - [i22]Thomas George, César Laurent, Xavier Bouthillier, Nicolas Ballas, Pascal Vincent:
Fast Approximate Natural Gradient Descent in a Kronecker-factored Eigenbasis. CoRR abs/1806.03884 (2018) - [i21]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:
fastMRI: An Open Dataset and Benchmarks for Accelerated MRI. CoRR abs/1811.08839 (2018) - 2017
- [c41]Samira Ebrahimi Kahou, Vincent Michalski, Roland Memisevic, Christopher Joseph Pal, Pascal Vincent:
RATM: Recurrent Attentive Tracking Model. CVPR Workshops 2017: 1613-1622 - [c40]Florian Bordes, Sina Honari, Pascal Vincent:
Learning to Generate Samples from Noise through Infusion Training. ICLR (Poster) 2017 - [c39]César Laurent, Nicolas Ballas, Pascal Vincent:
Recurrent Normalization Propagation. ICLR (Workshop) 2017 - [i20]Florian Bordes, Sina Honari, Pascal Vincent:
Learning to Generate Samples from Noise through Infusion Training. CoRR abs/1703.06975 (2017) - [i19]Ahmed Touati, Pierre-Luc Bacon, Doina Precup, Pascal Vincent:
Convergent Tree-Backup and Retrace with Function Approximation. CoRR abs/1705.09322 (2017) - [i18]Dzmitry Bahdanau, Tom Bosc, Stanislaw Jastrzebski, Edward Grefenstette, Pascal Vincent, Yoshua Bengio:
Learning to Compute Word Embeddings On the Fly. CoRR abs/1706.00286 (2017) - [i17]Sina Honari, Pavlo Molchanov, Stephen Tyree, Pascal Vincent, Christopher Joseph Pal, Jan Kautz:
Improving Landmark Localization with Semi-Supervised Learning. CoRR abs/1709.01591 (2017) - 2016
- [j11]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:
EmoNets: Multimodal deep learning approaches for emotion recognition in video. J. Multimodal User Interfaces 10(2): 99-111 (2016) - [c38]Sina Honari, Jason Yosinski, Pascal Vincent, Christopher J. Pal:
Recombinator Networks: Learning Coarse-to-Fine Feature Aggregation. CVPR 2016: 5743-5752 - [c37]Alexandre de Brébisson, Pascal Vincent:
An Exploration of Softmax Alternatives Belonging to the Spherical Loss Family. ICLR (Poster) 2016 - [i16]Alexandre de Brébisson, Pascal Vincent:
The Z-loss: a shift and scale invariant classification loss belonging to the Spherical Family. CoRR abs/1604.08859 (2016) - [i15]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:
Theano: A Python framework for fast computation of mathematical expressions. CoRR abs/1605.02688 (2016) - [i14]Sarath Chandar, Sungjin Ahn, Hugo Larochelle, Pascal Vincent, Gerald Tesauro, Yoshua Bengio:
Hierarchical Memory Networks. CoRR abs/1605.07427 (2016) - [i13]Pascal Vincent, Alexandre de Brébisson, Xavier Bouthillier:
Exact gradient updates in time independent of output size for the spherical loss family. CoRR abs/1606.08061 (2016) - [i12]Alexandre de Brébisson, Pascal Vincent:
A Cheap Linear Attention Mechanism with Fast Lookups and Fixed-Size Representations. CoRR abs/1609.05866 (2016) - 2015
- [c36]Pascal Vincent, Alexandre de Brébisson, Xavier Bouthillier:
Efficient Exact Gradient Update for training Deep Networks with Very Large Sparse Targets. NIPS 2015: 1108-1116 - [c35]Alexandre de Brébisson, Étienne Simon, Alex Auvolat, Pascal Vincent, Yoshua Bengio:
Artificial Neural Networks Applied to Taxi Destination Prediction. DC@PKDD/ECML 2015 - [c34]Pascal Vincent:
Efficient Exact Gradient Update for training Deep Networks with Very Large Sparse Targets. ICLR (Workshop) 2015 - [i11]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:
EmoNets: Multimodal deep learning approaches for emotion recognition in video. CoRR abs/1503.01800 (2015) - [i10]Guillaume Alain, Yoshua Bengio, Li Yao, Jason Yosinski, Eric Thibodeau-Laufer, Saizheng Zhang, Pascal Vincent:
GSNs : Generative Stochastic Networks. CoRR abs/1503.05571 (2015) - [i9]Kishore Reddy Konda, Xavier Bouthillier, Roland Memisevic, Pascal Vincent:
Dropout as data augmentation. CoRR abs/1506.08700 (2015) - [i8]Alex Auvolat, Pascal Vincent:
Clustering is Efficient for Approximate Maximum Inner Product Search. CoRR abs/1507.05910 (2015) - [i7]Alexandre de Brébisson, Étienne Simon, Alex Auvolat, Pascal Vincent, Yoshua Bengio:
Artificial Neural Networks Applied to Taxi Destination Prediction. CoRR abs/1508.00021 (2015) - [i6]Sina Honari, Jason Yosinski, Pascal Vincent, Christopher J. Pal:
Recombinator Networks: Learning Coarse-to-Fine Feature Aggregation. CoRR abs/1511.07356 (2015) - 2013
- [j10]Yoshua Bengio, Aaron C. Courville, Pascal Vincent:
Representation Learning: A Review and New Perspectives. IEEE Trans. Pattern Anal. Mach. Intell. 35(8): 1798-1828 (2013) - [c33]Nicolas Boulanger-Lewandowski, Yoshua Bengio, Pascal Vincent:
High-dimensional sequence transduction. ICASSP 2013: 3178-3182 - [c32]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:
Combining modality specific deep neural networks for emotion recognition in video. ICMI 2013: 543-550 - [c31]Hani Almousli, Pascal Vincent:
Semi Supervised Autoencoders: Better Focusing Model Capacity during Feature Extraction. ICONIP (1) 2013: 328-335 - [c30]Grégoire Mesnil, Salah Rifai, Antoine Bordes, Xavier Glorot, Yoshua Bengio, Pascal Vincent:
Unsupervised Learning of Semantics of Object Detections for Scene Categorization. ICPRAM (Selected Papers) 2013: 209-224 - [c29]Grégoire Mesnil, Salah Rifai, Antoine Bordes, Xavier Glorot, Yoshua Bengio, Pascal Vincent:
Unsupervised and Transfer Learning under Uncertainty - From Object Detections to Scene Categorization. ICPRAM 2013: 345-354 - [c28]Nicolas Boulanger-Lewandowski, Yoshua Bengio, Pascal Vincent:
Audio Chord Recognition with Recurrent Neural Networks. ISMIR 2013: 335-340 - [c27]Yoshua Bengio, Li Yao, Guillaume Alain, Pascal Vincent:
Generalized Denoising Auto-Encoders as Generative Models. NIPS 2013: 899-907 - [i5]Yoshua Bengio, Li Yao, Guillaume Alain, Pascal Vincent:
Generalized Denoising Auto-Encoders as Generative Models. CoRR abs/1305.6663 (2013) - 2012
- [c26]Salah Rifai, Yoshua Bengio, Aaron C. Courville, Pascal Vincent, Mehdi Mirza:
Disentangling Factors of Variation for Facial Expression Recognition. ECCV (6) 2012: 808-822 - [c25]Nicolas Boulanger-Lewandowski, Yoshua Bengio, Pascal Vincent:
Modeling Temporal Dependencies in High-Dimensional Sequences: Application to Polyphonic Music Generation and Transcription. ICML 2012 - [c24]Salah Rifai, Yann N. Dauphin, Pascal Vincent, Yoshua Bengio:
A Generative Process for Contractive Auto-Encoders. ICML 2012 - [c23]Nicolas Boulanger-Lewandowski, Yoshua Bengio, Pascal Vincent:
Discriminative Non-negative Matrix Factorization for Multiple Pitch Estimation. ISMIR 2012: 205-210 - [c22]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:
Unsupervised and Transfer Learning Challenge: a Deep Learning Approach. ICML Unsupervised and Transfer Learning 2012: 97-110 - [i4]Yoshua Bengio, Aaron C. Courville, Pascal Vincent:
Unsupervised Feature Learning and Deep Learning: A Review and New Perspectives. CoRR abs/1206.5538 (2012) - [i3]Nicolas Boulanger-Lewandowski, Yoshua Bengio, Pascal Vincent:
High-dimensional sequence transduction. CoRR abs/1212.1936 (2012) - 2011
- [j9]Charles Dugas, Nicolas Chapados, Réjean Ducharme, Xavier Saint-Mleux, Pascal Vincent:
A high-order feature synthesis and selection algorithm applied to insurance risk modelling. Int. J. Bus. Intell. Data Min. 6(3): 237-258 (2011) - [j8]Pascal Vincent:
A Connection Between Score Matching and Denoising Autoencoders. Neural Comput. 23(7): 1661-1674 (2011) - [j7]Olivier Breuleux, Yoshua Bengio, Pascal Vincent:
Quickly Generating Representative Samples from an RBM-Derived Process. Neural Comput. 23(8): 2058-2073 (2011) - [c21]Salah Rifai, Pascal Vincent, Xavier Muller, Xavier Glorot, Yoshua Bengio:
Contractive Auto-Encoders: Explicit Invariance During Feature Extraction. ICML 2011: 833-840 - [c20]Samuel Guillon, Daisuke Saya, Laurent Mazenq, Liviu Nicu, Sorin Perisanu, Pascal Vincent:
Fabrication and characterization of 100-nm wide silicon nanocantilevers using top-down approach. NEMS 2011: 258-261 - [c19]Salah Rifai, Yann N. Dauphin, Pascal Vincent, Yoshua Bengio, Xavier Muller:
The Manifold Tangent Classifier. NIPS 2011: 2294-2302 - [c18]Salah Rifai, Grégoire Mesnil, Pascal Vincent, Xavier Muller, Yoshua Bengio, Yann N. Dauphin, Xavier Glorot:
Higher Order Contractive Auto-Encoder. ECML/PKDD (2) 2011: 645-660 - [i2]Salah Rifai, Xavier Glorot, Yoshua Bengio, Pascal Vincent:
Adding noise to the input of a model trained with a regularized objective. CoRR abs/1104.3250 (2011) - [i1]Salah Rifai, Xavier Muller, Xavier Glorot, Grégoire Mesnil, Yoshua Bengio, Pascal Vincent:
Learning invariant features through local space contraction. CoRR abs/1104.4153 (2011) - 2010
- [j6]Dumitru Erhan, Yoshua Bengio, Aaron C. Courville, Pierre-Antoine Manzagol, Pascal Vincent, Samy Bengio:
Why Does Unsupervised Pre-training Help Deep Learning? J. Mach. Learn. Res. 11: 625-660 (2010) - [j5]Pascal Vincent, Hugo Larochelle, Isabelle Lajoie, Yoshua Bengio, Pierre-Antoine Manzagol:
Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion. J. Mach. Learn. Res. 11: 3371-3408 (2010) - [c17]Guillaume Desjardins, Aaron C. Courville, Yoshua Bengio, Pascal Vincent, Olivier Delalleau:
Tempered Markov Chain Monte Carlo for training of Restricted Boltzmann Machines. AISTATS 2010: 145-152 - [c16]Dumitru Erhan, Aaron C. Courville, Yoshua Bengio, Pascal Vincent:
Why Does Unsupervised Pre-training Help Deep Learning? AISTATS 2010: 201-208
2000 – 2009
- 2009
- [c15]Dumitru Erhan, Pierre-Antoine Manzagol, Yoshua Bengio, Samy Bengio, Pascal Vincent:
The Difficulty of Training Deep Architectures and the Effect of Unsupervised Pre-Training. AISTATS 2009: 153-160 - [c14]Hugo Larochelle, Dumitru Erhan, Pascal Vincent:
Deep Learning using Robust Interdependent Codes. AISTATS 2009: 312-319 - 2008
- [c13]Nicolas Chapados, Charles Dugas, Pascal Vincent, Réjean Ducharme:
Scoring Models for Insurance Risk Sharing Pool Opimization. ICDM Workshops 2008: 97-105 - [c12]Pascal Vincent, Hugo Larochelle, Yoshua Bengio, Pierre-Antoine Manzagol:
Extracting and composing robust features with denoising autoencoders. ICML 2008: 1096-1103 - 2007
- [j4]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:
The Need for Open Source Software in Machine Learning. J. Mach. Learn. Res. 8: 2443-2466 (2007) - 2006
- [p1]Yoshua Bengio, Olivier Delalleau, Nicolas Le Roux, Jean-François Paiement, Pascal Vincent, Marie Ouimet:
Spectral Dimensionality Reduction. Feature Extraction 2006: 519-550 - 2005
- [c11]Yoshua Bengio, Hugo Larochelle, Pascal Vincent:
Non-Local Manifold Parzen Windows. NIPS 2005: 115-122 - [c10]Yoshua Bengio, Nicolas Le Roux, Pascal Vincent, Olivier Delalleau, Patrice Marcotte:
Convex Neural Networks. NIPS 2005: 123-130 - 2004
- [j3]Yoshua Bengio, Olivier Delalleau, Nicolas Le Roux, Jean-François Paiement, Pascal Vincent, Marie Ouimet:
Learning Eigenfunctions Links Spectral Embedding and Kernel PCA. Neural Comput. 16(10): 2197-2219 (2004) - 2003
- [j2]Yoshua Bengio, Réjean Ducharme, Pascal Vincent, Christian Janvin:
A Neural Probabilistic Language Model. J. Mach. Learn. Res. 3: 1137-1155 (2003) - [c9]Yoshua Bengio, Jean-François Paiement, Pascal Vincent, Olivier Delalleau, Nicolas Le Roux, Marie Ouimet:
Out-of-Sample Extensions for LLE, Isomap, MDS, Eigenmaps, and Spectral Clustering. NIPS 2003: 177-184 - 2002
- [j1]Pascal Vincent, Yoshua Bengio:
Kernel Matching Pursuit. Mach. Learn. 48(1-3): 165-187 (2002) - [c8]Pascal Vincent, Yoshua Bengio:
Manifold Parzen Windows. NIPS 2002: 825-832 - 2001
- [c7]Pascal Vincent, Yoshua Bengio:
K-Local Hyperplane and Convex Distance Nearest Neighbor Algorithms. NIPS 2001: 985-992 - [c6]Nicolas Chapados, Yoshua Bengio, Pascal Vincent, Joumana Ghosn, Charles Dugas, Ichiro Takeuchi, Linyan Meng:
Estimating Car Insurance Premia: a Case Study in High-Dimensional Data Inference. NIPS 2001: 1369-1376 - [c5]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:
ROBOSIX UPMC-CFA: RoboCup Team Description. RoboCup 2001: 665-668 - 2000
- [c4]Pascal Vincent, Yoshua Bengio:
A Neural Support Vector Network Architecture with Adaptive Kernels. IJCNN (5) 2000: 187-192 - [c3]Yoshua Bengio, Réjean Ducharme, Pascal Vincent:
A Neural Probabilistic Language Model. NIPS 2000: 932-938
1990 – 1999
- 1999
- [c2]Patrick Haffner, Yann LeCun, Léon Bottou, Paul G. Howard, Pascal Vincent, Bill Riemers:
Color Documents on the Web with DJVU. ICIP (1) 1999: 239-243 - 1990
- [c1]Patrick Thévenoux, Pascal Vincent:
Region Tracking through Neural Classifier. MVA 1990: 275-278
Coauthor Index
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