← Authors

Ilya Sutskever

39 papers · 2008–2025 · 7 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (6) 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge πŸƒ Academic Marathon (17) πŸ—ΊοΈ Taxonomy Completionist (24) 🌍 Conference Polyglot (7) 🧭 Keyword Pioneer 🌟 Keyword Trendsetter Combo (22) πŸ‘‘ Triple Crown πŸ† Keyword Champion πŸ‘₯ Mega-Team (31) 🌱 Topic Pioneer 🧬 Topic Evolution πŸ—ƒοΈ Keyword Collector (75) πŸ’Ž Century Club (39) πŸš€ Conference Pioneer πŸ“ˆ Trend Setter πŸ”₯ Unstoppable (14)

Conferences

NIPS (14) ICML (12) ICLR (8) AISTATS (2) ACL (1) IJCNLP (1) JMLR (1)

Top co-authors

Alec Radford (7) Mark Chen (6) Aditya Ramesh (5) Oriol Vinyals (5) Wojciech Zaremba (4) Jeffrey Wu (4) Pieter Abbeel (4) Prafulla Dhariwal (4) Rewon Child (3) Yan Duan (3)

Keywords

restricted boltzmann machine (4) representation learning (3) generative model (3) autoregressive model (3) image generation (3) deep neural network (3) few-shot learning (2) unsupervised learning (2) zero-shot learning (2) stochastic gradient descent (2) long short-term memory (2) recurrent neural network (2) probabilistic model (2) probabilistic inference (2) markov random field (2) diffusion model (2) feature learning (1) metric learning (1) sequence generation (1) probabilistic modeling (1)

Papers

Scaling and evaluating sparse autoencoders ICLR 2025
Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision ICML 2024
Let's Verify Step by Step ICLR 2024
Consistency Models ICML 2023
Formal Mathematics Statement Curriculum Learning ICLR 2023
Robust Speech Recognition via Large-Scale Weak Supervision ICML 2023
GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models ICML 2022
Learning Transferable Visual Models From Natural Language Supervision ICML 2021
Zero-Shot Text-to-Image Generation ICML 2021
Generative Pretraining From Pixels ICML 2020
Language Models are Few-Shot Learners NIPS 2020
Deep Double Descent: Where Bigger Models and More Data Hurt ICLR 2020
Distribution Augmentation for Generative Modeling ICML 2020
FFJORD: Free-Form Continuous Dynamics for Scalable Reversible Generative Models ICLR 2019
GamePad: A Learning Environment for Theorem Proving ICLR 2019
The Importance of Sampling inMeta-Reinforcement Learning NIPS 2018
Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments ICLR 2018
Emergent Complexity via Multi-Agent Competition ICLR 2018
One-Shot Imitation Learning NIPS 2017
InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets NIPS 2016
Continuous Deep Q-Learning with Model-based Acceleration ICML 2016
Improved Variational Inference with Inverse Autoregressive Flow NIPS 2016
An Online Sequence-to-Sequence Model Using Partial Conditioning NIPS 2016
Addressing the Rare Word Problem in Neural Machine Translation IJCNLP 2015
Addressing the Rare Word Problem in Neural Machine Translation ACL 2015
An Empirical Exploration of Recurrent Network Architectures ICML 2015
Grammar as a Foreign Language NIPS 2015
Dropout: A Simple Way to Prevent Neural Networks from Overfitting JMLR 2014
Sequence to Sequence Learning with Neural Networks NIPS 2014
Distributed Representations of Words and Phrases and their Compositionality NIPS 2013
Stochastic k-Neighborhood Selection for Supervised and Unsupervised Learning ICML 2013
On the importance of initialization and momentum in deep learning ICML 2013
ImageNet Classification with Deep Convolutional Neural Networks NIPS 2012
Cardinality Restricted Boltzmann Machines NIPS 2012
On the Convergence Properties of Contrastive Divergence AISTATS 2010
Parallelizable Sampling of Markov Random Fields AISTATS 2010
Modelling Relational Data using Bayesian Clustered Tensor Factorization NIPS 2009
The Recurrent Temporal Restricted Boltzmann Machine NIPS 2008
Using matrices to model symbolic relationship NIPS 2008