Pascal Vincent

发表

Improving Landmark Localization with Semi-Supervised Learning

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

A Neural Support Vector Network architecture with adaptive kernels

Pascal Vincent, Yoshua Bengio, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

Fast Approximate Natural Gradient Descent in a Kronecker-factored Eigenbasis

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

Non-Local Manifold Parzen Windows

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

Recurrent Normalization Propagation

Pascal Vincent, César Laurent, Nicolas Ballas, 2017, ICLR.

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

Pascal Vincent, Liviu Nicu, Daisuke Saya, 2011, 2011 6th IEEE International Conference on Nano/Micro Engineered and Molecular Systems.

The Need for Open Source Software in Machine Learning

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

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).

Learning Eigenfunctions Links Spectral Embedding and Kernel PCA

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

K-Local Hyperplane and Convex Distance Nearest Neighbor Algorithms

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

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.

Hierarchical Memory Networks pdf

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

Statistical Learning Algorithms Applied to Automobile Insurance Ratemaking

Pascal Vincent, Nicolas Chapados, Yoshua Bengio, 2003 .

Learning to Compute Word Embeddings On the Fly pdf

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

Scoring Models for Insurance Risk Sharing Pool Opimization

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

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

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

SVRG for Policy Evaluation with Fewer Gradient Evaluations pdf

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

Deep Learning using Robust Interdependent Codes

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

A Generative Process for Contractive Auto-Encoders

Pascal Vincent, Yoshua Bengio, Yann Dauphin, 2012, ICML.

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

Pascal Vincent, Alexandre de Brébisson, 2016, ArXiv.

Higher Order Contractive Auto-Encoder

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

Kernel Matching Pursuit

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

Spectral Dimensionality Reduction

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

A Common GPU n-Dimensional Array for Python and C

Pascal Vincent, Yoshua Bengio, Arnaud Bergeron, 2011 .

Unsupervised Learning of Semantics of Object Detections for Scene Categorization

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

ATV Thermal Operations for Jules Verne First Flight

Pascal Vincent, Frank Bouckaert, Patrick Oger, 2009 .

A Connection Between Score Matching and Denoising Autoencoders

Pascal Vincent, Pascal Vincent, 2011, Neural Computation.

Dropout as data augmentation pdf

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

Disentangling Factors of Variation for Facial Expression Recognition

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

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

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

Randomized Value Functions via Multiplicative Normalizing Flows

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

Visualizing Higher-Layer Features of a Deep Network

Pascal Vincent, Yoshua Bengio, Dumitru Erhan, 2009 .

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

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

Generalized Denoising Auto-Encoders as Generative Models

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

Representation Learning: A Review and New Perspectives

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

Contractive Auto-Encoders: Explicit Invariance During Feature Extraction

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

Iteratively unveiling new regions of interest in Deep Learning models

Pascal Vincent, Yoshua Bengio, Florian Bordes, 2018 .

GSNs : Generative Stochastic Networks pdf

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

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.

Semi Supervised Autoencoders: Better Focusing Model Capacity during Feature Extraction

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

An Evaluation of Fisher Approximations Beyond Kronecker Factorization

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

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

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

Clustering is Efficient for Approximate Maximum Inner Product Search pdf

Pascal Vincent, Alex Auvolat, 2015, ArXiv.

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..

Discriminative Non-negative Matrix Factorization for Multiple Pitch Estimation

Pascal Vincent, Yoshua Bengio, Nicolas Boulanger-Lewandowski, 2012, ISMIR.

Thermal - Power - Software Development and Validation on ATV Vehicle

Pascal Vincent, Frank Bouckaert, Patrick Oger, 2009 .

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

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

Learning invariant features through local space contraction pdf

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

The Manifold Tangent Classifier

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

Color documents on the Web with DjVu

Pascal Vincent, Yann LeCun, Léon Bottou, 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

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

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

ROBOSIX UPMC-CFA: RoboCup Team Description

Pascal Vincent, Ryad Benosman, Xavier Vasseur, 2001, RoboCup.

Artificial Neural Networks Applied to Taxi Destination Prediction pdf

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

Parallel Tempering for Training of Restricted Boltzmann Machines

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

Stochastic Neural Network with Kronecker Flow

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

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).

Tempered Markov Chain Monte Carlo for training of Restricted Boltzmann Machines

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

Manifold Parzen Windows

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

ATV THERMAL CONTROL: Architecture and Jules Verne First Flight Results

Pascal Vincent, Frank Bouckaert, Patrick Oger, 2009 .

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

Pascal Vincent, Doina Precup, Chris Pal, 2019, ArXiv.

Region Tracking through Neural Classifier

Pascal Vincent, Patrick Thévenoux, 1990, MVA.

Convex Neural Networks

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

Quickly Generating Representative Samples from an RBM-Derived Process

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

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

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

fastMRI: An Open Dataset and Benchmarks for Accelerated MRI pdf

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

Learning to Generate Samples from Noise through Infusion Training pdf

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

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

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

Auto-Encoding Dictionary Definitions into Consistent Word Embeddings

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

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

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

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

Pascal Vincent, Florian Bordes, Randall Balestriero, 2021, ArXiv.