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← Authors

Ilya Sutskever

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

Achievements

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+14 more ↓ 🧭 Keyword Pioneer 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (24) 🐣 Hot Topic Early Bird
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