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Pascal Vincent

41 papers · 2003–2025 · 11 conferences · across top CS/AI conferences

Achievements

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+15 more ↓ 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (14) 🧭 Keyword Pioneer πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (11)
πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (14) 🌟 Keyword Trendsetter Combo (4) πŸ‘‘ Triple Crown 🧬 Topic Evolution πŸ† Keyword Champion 🌱 Topic Pioneer πŸ’Ž Century Club (41) ⚑ Prolific Year (6) πŸš€ Conference Pioneer πŸ“ˆ Trend Setter ❓ The Questioner (4) πŸ”₯ Unstoppable (8) πŸ—ƒοΈ Keyword Collector (144)

Conferences

ICLR (10) NIPS (7) ICML (6) AISTATS (4) CVPR (4) JMLR (3) EMNLP (2) UAI (2) CLEAR (1) ECCV (1) IJCAI (1)

Top co-authors

Nicolas Ballas (7) Simon Lacoste-Julien (7) Yoshua Bengio (7) Florian Bordes (5) Ahmed Touati (5) Hugo Berard (5) Aaron Courville (4) Diane Bouchacourt (4) Gauthier Gidel (4) Mark Ibrahim (4)

Keywords

representation learning (7) neural network (3) semi-supervised learning (2) denoising autoencoder (2) unsupervised pre-training (2) deep belief network (2) gradient descent (2) self-supervised learning (2) thompson sampling (2) unsupervised learning (2) contractive autoencoders (2) feature learning (2) language model (2) word embedding (2) deep reinforcement learning (2) variational inference (2) deep learning (2) markov chain monte carlo (2) image generation (1) policy evaluation (1)

Papers

The Pitfalls of Memorization: When Memorization Hurts Generalization ICLR 2025 MaestroMotif: Skill Design from Artificial Intelligence Feedback ICLR 2025 Compositional Risk Minimization ICML 2025 Discovering Environments with XRM ICML 2024 On the Identifiability of Quantized Factors CLEAR 2024 Motif: Intrinsic Motivation from Artificial Intelligence Feedback ICLR 2024 Stochastic positional embeddings improve masked image modeling ICML 2024 Self-Supervised Learning From Images With a Joint-Embedding Predictive Architecture CVPR 2023 Do SSL Models Have DΓ©jΓ  Vu? A Case of Unintended Memorization in Self-supervised Learning NIPS 2023 PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning NIPS 2023 ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations ICLR 2023 The hidden uniform cluster prior in self-supervised learning ICLR 2023 Disentanglement of Correlated Factors via Hausdorff Factorized Support ICLR 2023 Understanding Dimensional Collapse in Contrastive Self-supervised Learning ICLR 2022 Online Adversarial Attacks ICLR 2022 Masked Siamese Networks for Label-Efficient Learning ECCV 2022 Implicit Regularization via Neural Feature Alignment AISTATS 2021 Stochastic Hamiltonian Gradient Methods for Smooth Games ICML 2020 Stable Policy Optimization via Off-Policy Divergence Regularization UAI 2020 Stochastic Neural Network with Kronecker Flow AISTATS 2020 SVRG for Policy Evaluation with Fewer Gradient Evaluations IJCAI 2020 Adversarial Example Games NIPS 2020 A Closer Look at the Optimization Landscapes of Generative Adversarial Networks ICLR 2020 Do sequence-to-sequence VAEs learn global features of sentences? EMNLP 2020 A Variational Inequality Perspective on Generative Adversarial Networks ICLR 2019 Unreproducible Research is Reproducible ICML 2019 Randomized Value Functions via Multiplicative Normalizing Flows UAI 2019 Reducing Uncertainty in Undersampled MRI Reconstruction With Active Acquisition CVPR 2019 Convergent Tree Backup and Retrace with Function Approximation ICML 2018 Improving Landmark Localization With Semi-Supervised Learning CVPR 2018 Auto-Encoding Dictionary Definitions into Consistent Word Embeddings EMNLP 2018 Fast Approximate Natural Gradient Descent in a Kronecker Factored Eigenbasis NIPS 2018 Recombinator Networks: Learning Coarse-To-Fine Feature Aggregation CVPR 2016 Efficient Exact Gradient Update for training Deep Networks with Very Large Sparse Targets NIPS 2015 Generalized Denoising Auto-Encoders as Generative Models NIPS 2013 The Manifold Tangent Classifier NIPS 2011 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 Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion JMLR 2010 A Neural Probabilistic Language Model JMLR 2003