Sylvain Gelly
24 papers · 2017–2021 · 9 conferences · across top CS/AI conferences
Achievements
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π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (39) π Conference Polyglot (9) π Renaissance Researcher (6) π§ Keyword Pioneer
πΊοΈ
Taxonomy Completionist
(39)
π
Cross-Pollinator
(15)
π€
Dynamic Duo
(11)
π
Triple Crown
π
Grand Slam
π₯
Unstoppable
(5)
π
Trend Setter
π
Century Club
(24)
π
Conference Pioneer
ποΈ
Keyword Collector
(70)
β‘
Prolific Year
(7)
β
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
Keywords
generative adversarial network
(5)
transfer learning
(4)
representation learning
(3)
unsupervised learning
(2)
semi-supervised learning
(2)
self-supervised learning
(2)
inductive bia
(2)
reinforcement learning
(2)
evaluation metric
(2)
precision and recall
(2)
generative model
(2)
disentangled representation
(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)
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