← Authors

Sylvain Gelly

24 papers · 2017–2021 · 9 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (9) πŸŒ‰ Interdisciplinary Bridge 🌈 Renaissance Researcher (6) 🐣 Hot Topic Early Bird 🧭 Keyword Pioneer πŸ—ΊοΈ Taxonomy Completionist (39) 🐝 Cross-Pollinator (15) 🀝 Dynamic Duo (11) πŸ‘‘ Triple Crown πŸ† Grand Slam πŸ”₯ Unstoppable (5) πŸ“ˆ Trend Setter πŸ’Ž Century Club (24) πŸš€ Conference Pioneer πŸ—ƒοΈ Keyword Collector (70) ⚑ Prolific Year (7) ❓ The Questioner (4)

Conferences

ICLR (7) ICML (5) NIPS (5) CVPR (2) AAAI (1) AISTATS (1) COLT (1) ECCV (1) JMLR (1)

Top co-authors

Mario Lucic (11) Olivier Bousquet (8) Olivier Bachem (7) Neil Houlsby (7) Xiaohua Zhai (5) Josip Djolonga (4) Marcin Michalski (4) Michael Tschannen (4) Alexander Kolesnikov (3) Joan Puigcerver (3)

Keywords

generative adversarial network (5) transfer learning (4) representation learning (3) self-supervised learning (2) disentangled representation (2) unsupervised learning (2) reinforcement learning (2) inductive bia (2) precision and recall (2) semi-supervised learning (2) generative model (2) model robustness (1) image generation (1) hyperparameter optimization (1) policy gradient (1) policy evaluation (1) text classification (1) neural architecture (1) matrix factorization (1) out-of-distribution generalization (1)

Papers

What Matters for On-Policy Deep Actor-Critic Methods? A Large-Scale Study ICLR 2021
Scalable Transfer Learning with Expert Models ICLR 2021
On Robustness and Transferability of Convolutional Neural Networks CVPR 2021
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale ICLR 2021
Google Research Football: A Novel Reinforcement Learning Environment AAAI 2020
Precision-Recall Curves Using Information Divergence Frontiers AISTATS 2020
Self-Supervised Learning of Video-Induced Visual Invariances CVPR 2020
Big Transfer (BiT): General Visual Representation Learning ECCV 2020
A Sober Look at the Unsupervised Learning of Disentangled Representations and their Evaluation JMLR 2020
On Mutual Information Maximization for Representation Learning ICLR 2020
What Do Neural Networks Learn When Trained With Random Labels? NIPS 2020
On Self Modulation for Generative Adversarial Networks ICLR 2019
Adaptive Temporal-Difference Learning for Policy Evaluation with Per-State Uncertainty Estimates NIPS 2019
When can unlabeled data improve the learning rate? COLT 2019
Episodic Curiosity through Reachability ICLR 2019
Parameter-Efficient Transfer Learning for NLP ICML 2019
A Large-Scale Study on Regularization and Normalization in GANs ICML 2019
Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations ICML 2019
High-Fidelity Image Generation With Fewer Labels ICML 2019
Breaking the Softmax Bottleneck via Learnable Monotonic Pointwise Non-linearities ICML 2019
Wasserstein Auto-Encoders ICLR 2018
Assessing Generative Models via Precision and Recall NIPS 2018
Are GANs Created Equal? A Large-Scale Study NIPS 2018
AdaGAN: Boosting Generative Models NIPS 2017