Pascal Vincent

发表

Visualizing Higher-Layer Features of a Deep Network

Pascal Vincent, Yoshua Bengio, Dumitru Erhan, 2009 .

Learning Eigenfunctions Links Spectral Embedding and Kernel PCA

Nicolas Le Roux, Pascal Vincent, Jean-François Paiement, 2004, Neural Computation.

Nicolas Le Roux, Pascal Vincent, Yoshua Bengio, 2005, NIPS.

Representation Learning: A Review and New Perspectives

Pascal Vincent, Yoshua Bengio, Aaron C. Courville, 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion

Pascal Vincent, Yoshua Bengio, Hugo Larochelle, 2010, J. Mach. Learn. Res..

Generalized Denoising Auto-Encoders as Generative Models

Pascal Vincent, Li Yao, Yoshua Bengio, 2013, NIPS.

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

Pascal Vincent, Samy Bengio, Yoshua Bengio, 2009, AISTATS.

Quickly Generating Representative Samples from an RBM-Derived Process

Pascal Vincent, Yoshua Bengio, Olivier Breuleux, 2011, Neural Computation.

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

Pascal Vincent, Yoshua Bengio, Aaron C. Courville, 2012, ArXiv.

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

Pascal Vincent, Yoshua Bengio, Antoine Bordes, 2013, ICPRAM.

Contractive Auto-Encoders: Explicit Invariance During Feature Extraction

Pascal Vincent, Yoshua Bengio, Salah Rifai, 2011, ICML.

Recombinator Networks: Learning Coarse-to-Fine Feature Aggregation

Sina Honari, Pascal Vincent, Christopher Joseph Pal, 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Disentangling Factors of Variation for Facial Expression Recognition

Pascal Vincent, Yoshua Bengio, Aaron C. Courville, 2012, ECCV.

Manifold Parzen Windows

Pascal Vincent, Yoshua Bengio, Yoshua Bengio, 2002, NIPS.

Higher Order Contractive Auto-Encoder

Pascal Vincent, Yoshua Bengio, Yann Dauphin, 2011, ECML/PKDD.

The Manifold Tangent Classifier

Pascal Vincent, Yoshua Bengio, Yann Dauphin, 2011, NIPS.

A Connection Between Score Matching and Denoising Autoencoders

Pascal Vincent, Pascal Vincent, 2011, Neural Computation.

The Need for Open Source Software in Machine Learning

Carl E. Rasmussen, Gunnar Rätsch, Bernhard Schölkopf, 2007, J. Mach. Learn. Res..

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

Pascal Vincent, Yoshua Bengio, Salah Rifai, 2011, ArXiv.

Non-Local Manifold Parzen Windows

Pascal Vincent, Yoshua Bengio, Hugo Larochelle, 2005, NIPS.

Deep Learning using Robust Interdependent Codes

Pascal Vincent, Dumitru Erhan, Hugo Larochelle, 2009, AISTATS.

Tempered Markov Chain Monte Carlo for training of Restricted Boltzmann Machines

Pascal Vincent, Yoshua Bengio, Aaron C. Courville, 2010, AISTATS.

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

Nicolas Le Roux, Pascal Vincent, Jean-François Paiement, 2003, NIPS.

Spectral Clustering and Kernel PCA are Learning Eigenfunctions

Yoshua Bengio, Pascal Vincent, Jean-François Paiement, 2003 .

Convergent Tree-Backup and Retrace with Function Approximation pdf

Pascal Vincent, Doina Precup, Pierre-Luc Bacon, 2017, ICML.

Unreproducible Research is Reproducible

Pascal Vincent, César Laurent, Xavier Bouthillier, 2019, ICML.

Dropout as data augmentation pdf

Pascal Vincent, Roland Memisevic, Kishore Reddy Konda, 2015, ArXiv.

Unsupervised Learning of Semantics of Object Detections for Scene Categorization

Pascal Vincent, Yoshua Bengio, Antoine Bordes, 2013, ICPRAM.

Learning Eigenfunctions of Similarity: Linking Spectral Clustering and Kernel PCA

Yoshua Bengio, Pascal Vincent, Recherche Op, 2003 .

K-Local Hyperplane and Convex Distance Nearest Neighbor Algorithms

Pascal Vincent, Yoshua Bengio, Yoshua Bengio, 2001, NIPS.

Spectral Dimensionality Reduction

Nicolas Le Roux, Pascal Vincent, Jean-François Paiement, 2006, Feature Extraction.

Artificial Neural Networks Applied to Taxi Destination Prediction pdf

Pascal Vincent, Yoshua Bengio, Alexandre de Brébisson, 2015, DC@PKDD/ECML.

Learning to Compute Word Embeddings On the Fly pdf

Pascal Vincent, Yoshua Bengio, Edward Grefenstette, 2017, ArXiv.

Learning to Generate Samples from Noise through Infusion Training pdf

Sina Honari, Pascal Vincent, Florian Bordes, 2017, ICLR.

Locally Weighted Full Covariance Gaussian Density Estimation

Yoshua Bengio, Pascal Vincent, 2004 .

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

Pascal Vincent, Nicolas Chapados, Yoshua Bengio, 2001, NIPS.

Guillotine Regularization: Improving Deep Networks Generalization by Removing their Head

Pascal Vincent, Randall Balestriero, Florian Bordes, 2022, ArXiv.

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

Pascal Vincent, Randall Balestriero, Florian Bordes, 2021, Trans. Mach. Learn. Res..

Disentanglement of Correlated Factors via Hausdorff Factorized Support

Pascal Vincent, Zeynep Akata, Diane Bouchacourt, 2022, ArXiv.

The Hidden Uniform Cluster Prior in Self-Supervised Learning

Michael G. Rabbat, Pascal Vincent, Nicolas Ballas, 2022, ICLR.

Disentanglement of Correlated Factors via Hausdorff Factorized Support

Pascal Vincent, Zeynep Akata, Diane Bouchacourt, 2022, ArXiv.

The Emergence of Argument Structure in Artificial Languages

Pascal Vincent, Tom Bosc, 2022, Transactions of the Association for Computational Linguistics.

Semi Supervised Autoencoders: Better Focusing Model Capacity during Feature Extraction

Pascal Vincent, Hani Almousli, Pascal Vincent, 2013, ICONIP.

Learning invariant features through local space contraction pdf

Pascal Vincent, Yoshua Bengio, Grégoire Mesnil, 2011, ArXiv.

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

Pascal Vincent, Xavier Bouthillier, Alexandre de Brébisson, 2016, ArXiv.

Statistical Learning Algorithms Applied to Automobile Insurance Ratemaking

Pascal Vincent, Nicolas Chapados, Yoshua Bengio, 2003 .

Reducing Uncertainty in Undersampled MRI Reconstruction With Active Acquisition

Pascal Vincent, Lin Yang, Adriana Romero, 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

fastMRI: An Open Dataset and Benchmarks for Accelerated MRI pdf

Pascal Vincent, James Pinkerton, Duo Wang, 2018, ArXiv.

Hierarchical Memory Networks pdf

Pascal Vincent, Yoshua Bengio, Hugo Larochelle, 2016, ArXiv.

Stochastic Neural Network with Kronecker Flow

Pascal Vincent, Alexandre Lacoste, Gintare Karolina Dziugaite, 2019, AISTATS.

Fast Approximate Natural Gradient Descent in a Kronecker-factored Eigenbasis

Pascal Vincent, César Laurent, Nicolas Ballas, 2018, NeurIPS.

Kernel Matching Pursuit

Pascal Vincent, Yoshua Bengio, Yoshua Bengio, 2002, Machine Learning.

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

Pascal Vincent, Alexandre de Brébisson, Pascal Vincent, 2015, ICLR.

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

Badr Youbi Idrissi, Pascal Vincent, Nicolas Ballas, 2022, ICLR.

GSNs : Generative Stochastic Networks pdf

Pascal Vincent, Li Yao, Yoshua Bengio, 2015, ArXiv.

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

Pascal Vincent, Nicolas Ballas, Randall Balestriero, 2023, ArXiv.

Improving Landmark Localization with Semi-Supervised Learning

Sina Honari, Pavlo Molchanov, Stephen Tyree, 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

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

Ari S. Morcos, Pascal Vincent, Florian Bordes, 2023, ArXiv.

L EARNING TO G ENERATE S AMPLES FROM N OISE THROUGH I NFUSION T RAINING

Pascal Vincent, Florian Bordes, S. Honari, 2021 .

A Generative Process for sampling Contractive Auto-Encoders

Yoshua Bengio, Salah Rifai, Pascal Vincent, 2012, ICML 2012.

An Evaluation of Fisher Approximations Beyond Kronecker Factorization

Pascal Vincent, César Laurent, Nicolas Ballas, 2018, ICLR.

Towards Democratizing Joint-Embedding Self-Supervised Learning

Pascal Vincent, Randall Balestriero, Florian Bordes, 2023, arXiv.org.

Guillotine Regularization: Why removing layers is needed to improve generalization in Self-Supervised Learning

Pascal Vincent, Randall Balestriero, Florian Bordes, 2022, Trans. Mach. Learn. Res..

Parallel Tempering for Training of Restricted Boltzmann Machines

Pascal Vincent, Yoshua Bengio, Aaron C. Courville, 2010 .

GOOD TASK LOSSES FOR GENERATIVE MODELING

Pascal Vincent, S. Lacoste-Julien, Gauthier Gidel, 2018 .

Auto-Encoding Dictionary Definitions into Consistent Word Embeddings

Pascal Vincent, Tom Bosc, Pascal Vincent, 2018, EMNLP.

Instance-Conditioned GAN Data Augmentation for Representation Learning

Pascal Vincent, Jakob Verbeek, Arantxa Casanova, 2023, ArXiv.

Randomized Value Functions via Multiplicative Normalizing Flows

Joelle Pineau, Pascal Vincent, Joshua Romoff, 2018, UAI.

SVRG for Policy Evaluation with Fewer Gradient Evaluations pdf

Pascal Vincent, Doina Precup, Ahmed Touati, 2019, IJCAI.

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

Pascal Vincent, Gauthier Gidel, Amjad Almahairi, 2019, ICLR.

Disentanglement of Correlated Factors via Hausdorff Factorized Support

Pascal Vincent, Zeynep Akata, Diane Bouchacourt, 2022, ICLR.

Iteratively unveiling new regions of interest in Deep Learning models

Pascal Vincent, Yoshua Bengio, Florian Bordes, 2018 .

A Variational Inequality Perspective on Generative Adversarial Nets

Pascal Vincent, S. Lacoste-Julien, Gauthier Gidel, 2018, ArXiv.

Sparse Covariance Coding

Aaron C. Courville, Yoshua, D. Erhan, 2008 .

Manifold Parzen Windows

Yoshua Bengio, Pascal Vincent, 2002, NIPS.

Limits on primordial black hole evaporation from H.E.S.S. observations.

Sylvia J. Zhu, Pascal Vincent, David Sánchez, 2021, Proceedings of 37th International Cosmic Ray Conference — PoS(ICRC2021).

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

Pascal Vincent, Alexandre de Brébisson, Pascal Vincent, 2016, ArXiv.

Scoring Models for Insurance Risk Sharing Pool Opimization

Pascal Vincent, Nicolas Chapados, Charles Dugas, 2008, 2008 IEEE International Conference on Data Mining Workshops.

On the Identifiability of Quantized Factors

Pascal Vincent, Kartik Ahuja, Vit'oria Barin-Pacela, 2023, 2306.16334.

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

Pascal Vincent, Alexandre de Brébisson, Pascal Vincent, 2016, ArXiv.

A neural probabilistic language model

Pascal Vincent, Réjean Ducharme, Christian Janvin, 2003 .