Pascal Vincent
43 papers · 2003–2025 · 11 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (71) π Academic Marathon Β· Ultra π Conference Polyglot Β· Gold π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
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Keyword Pioneer
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Keyword Trendsetter Combo
(5)
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(6)
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Unstoppable Β· Bronze
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The Questioner
(4)
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Prolific Year Β· Productive
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Century Club Β· Bronze
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Trend Setter
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Keyword Collector
(199)
Venues
Top co-authors
Research topics
Machine Learning
(36)
Deep Learning
(23)
Learning Types Β· Machine Learning
(23)
Optimization & Theory
(18)
Learning Types Β· Deep Learning
(14)
Artificial Intelligence
(12)
Core Methods
(9)
Architectures
(8)
Core AI
(8)
Models
(7)
Computer Vision
(6)
Application Areas
(6)
Reinforcement Learning
(4)
Analysis
(4)
Methods
(4)
Keywords
representation learning
(10)
self-supervised learning
(4)
distribution shift
(4)
reinforcement learning
(3)
gradient descent
(3)
deep learning
(3)
neural network
(3)
denoising autoencoder
(2)
contractive autoencoders
(2)
language model
(2)
unsupervised learning
(2)
semi-supervised learning
(2)
thompson sampling
(2)
black-box attack
(2)
markov chain monte carlo
(2)
unsupervised pretraining
(2)
data augmentation
(2)
deep reinforcement learning
(2)
feature learning
(2)
variational inference
(2)
Papers
Compositional Risk Minimization
ICML 2025
MaestroMotif: Skill Design from Artificial Intelligence Feedback
ICLR 2025
The Pitfalls of Memorization: When Memorization Hurts Generalization
ICLR 2025
Discovering Environments with XRM
ICML 2024
Motif: Intrinsic Motivation from Artificial Intelligence Feedback
ICLR 2024
On the Identifiability of Quantized Factors
CLeaR 2024
Stochastic positional embeddings improve masked image modeling
ICML 2024
Disentanglement of Correlated Factors via Hausdorff Factorized Support
ICLR 2023
Do SSL Models Have DΓ©jΓ Vu? A Case of Unintended Memorization in Self-supervised Learning
NeurIPS 2023
ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations
ICLR 2023
PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning
NeurIPS 2023
Self-Supervised Learning From Images With a Joint-Embedding Predictive Architecture
CVPR 2023
The hidden uniform cluster prior in self-supervised learning
ICLR 2023
Masked Siamese Networks for Label-Efficient Learning
ECCV 2022
Online Adversarial Attacks
ICLR 2022
Understanding Dimensional Collapse in Contrastive Self-supervised Learning
ICLR 2022
Implicit Regularization via Neural Feature Alignment
AISTATS 2021
A Closer Look at the Optimization Landscapes of Generative Adversarial Networks
ICLR 2020
Adversarial Example Games
NeurIPS 2020
Do sequence-to-sequence VAEs learn global features of sentences?
EMNLP 2020
Stable Policy Optimization via Off-Policy Divergence Regularization
UAI 2020
Stochastic Hamiltonian Gradient Methods for Smooth Games
ICML 2020
Stochastic Neural Network with Kronecker Flow
AISTATS 2020
SVRG for Policy Evaluation with Fewer Gradient Evaluations
IJCAI 2020
A Variational Inequality Perspective on Generative Adversarial Networks
ICLR 2019
Randomized Value Functions via Multiplicative Normalizing Flows
UAI 2019
Reducing Uncertainty in Undersampled MRI Reconstruction With Active Acquisition
CVPR 2019
Unreproducible Research is Reproducible
ICML 2019
Auto-Encoding Dictionary Definitions into Consistent Word Embeddings
EMNLP 2018
Convergent Tree Backup and Retrace with Function Approximation
ICML 2018
Fast Approximate Natural Gradient Descent in a Kronecker Factored Eigenbasis
NeurIPS 2018
Improving Landmark Localization With Semi-Supervised Learning
CVPR 2018
Recombinator Networks: Learning Coarse-To-Fine Feature Aggregation
CVPR 2016
Efficient Exact Gradient Update for training Deep Networks with Very Large Sparse Targets
NeurIPS 2015
Generalized Denoising Auto-Encoders as Generative Models
NeurIPS 2013
The Manifold Tangent Classifier
NeurIPS 2011
Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion
JMLR 2010
Tempered Markov Chain Monte Carlo for training of Restricted Boltzmann Machines
AISTATS 2010
Why Does Unsupervised Pre-training Help Deep Learning?
AISTATS 2010
Why Does Unsupervised Pre-training Help Deep Learning?
JMLR 2010
Deep Learning using Robust Interdependent Codes
AISTATS 2005
The Difficulty of Training Deep Architectures and the Effect of Unsupervised Pre-Training
AISTATS 2005
A Neural Probabilistic Language Model
JMLR 2003