🧑‍🔬 Ilya Sutskever — all works

49 works · ← Ilya Sutskever

1. Dropout: A Simple Way to Prevent Neural Networks from Overfitting ↗JMLR 15(56):1929–1958 · no summary yetNitish Srivastava et al.2014 · 34,422 citations
2. Distributed Representations of Words and Phrases and their CompositionalityarXiv:1310.4546Tomas Mikolov, Ilya Sutskever, Kai Chen, et al.2013 · 21,623 citations
3. Sequence to Sequence Learning with Neural NetworksarXiv:1409.3215Ilya Sutskever, Oriol Vinyals, Quoc V. Le2014 · 18,409 citations
4. Learning Transferable Visual Models From Natural Language SupervisionarXiv:2103.00020Alec Radford, Jong Wook Kim, Chris Hallacy, et al.2021 · 8,767 citations
5. Improving neural networks by preventing co-adaptation of feature detectors ↗arXiv:1207.0580 · no summary yetGeoffrey E. Hinton et al.2012 · 6,645 citations
6. Intriguing properties of neural networksarXiv:1312.6199Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, et al.2013 · 5,999 citations
7. ImageNet Classification with Deep Convolutional Neural NetworksNeurIPS 2012Alex Krizhevsky, Ilya Sutskever, Geoffrey E. Hinton2012 · 2,801 citations
8. Robust Speech Recognition via Large-Scale Weak SupervisionarXiv:2212.04356Alec Radford, Jong Wook Kim, Tao Xu, et al.2022 · 2,546 citations
9. Recurrent Neural Network RegularizationarXiv:1409.2329Wojciech Zaremba, Ilya Sutskever, Oriol Vinyals2014 · 2,412 citations
10. Exploiting Similarities among Languages for Machine Translation ↗arXiv:1309.4168 (2013) · no summary yetTomas Mikolov, Quoc V. Le, I. Sutskever2013 · 1,838 citations
11. Zero-Shot Text-to-Image GenerationarXiv:2102.12092Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, et al.2021 · 1,528 citations
12. An Empirical Exploration of Recurrent Network Architectures ↗no summary yetRafał Józefowicz, Wojciech Zaremba, Ilya Sutskever2015 · 1,415 citations
13. Let's Verify Step by SteparXiv:2305.20050Hunter Lightman, Vineet Kosaraju, Yura Burda, et al.2023 · 1,412 citations
14. InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets ↗arXiv (Cornell University) · no summary yetChen, Xi et al.2016 · 1,285 citations
15. GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models ↗arXiv (Cornell University) · no summary yetAlex Nichol et al.2021 · 1,180 citations
16. Generating Long Sequences with Sparse TransformersarXiv:1904.10509Rewon Child, Scott Gray, Alec Radford, et al.2019 · 967 citations
17. Addressing the Rare Word Problem in Neural Machine TranslationAnnual Meeting of the Association for Computational Linguistics (ACL)Thang Luong, Ilya Sutskever, Quoc Le, et al.2015 · 832 citations
18. Improved Variational Inference with Inverse Autoregressive Flow ↗neural information processing systems · no summary yetDurk Kingma et al.2016 · 812 citations
19. Grammar as a Foreign Language ↗arXiv:1412.7449 · no summary yetOriol Vinyals et al.2014 · 687 citations
20. Generative Pretraining From Pixels ↗International Conference on Machine Learning · no summary yetMark I-Cheng Chen et al.2020 · 614 citations
21. RL²: Fast Reinforcement Learning via Slow Reinforcement LearningarXiv:1611.02779Yan Duan, John Schulman, Xi Chen, et al.2016 · 524 citations
22. Learning to Generate Reviews and Discovering SentimentarXiv:1704.01444Alec Radford, Rafal Jozefowicz, Ilya Sutskever2017 · 474 citations
23. Learning to Execute ↗arXiv:1410.4615 · no summary yetWojciech Zaremba, Ilya Sutskever2014 · 388 citations
24. Multi-task Sequence to Sequence LearningarXiv:1511.06114Minh-Thang Luong, Quoc V. Le, Ilya Sutskever, et al.2015 · 321 citations
25. Neural GPUs Learn Algorithms ↗arXiv:1511.08228 · no summary yetŁukasz Kaiser, Ilya Sutskever2015 · 305 citations
26. Variational Lossy Autoencoder ↗arXiv (Cornell University) · no summary yetXi Chen et al.2016 · 285 citations
27. Adding Gradient Noise Improves Learning for Very Deep Networks ↗arXiv (Cornell University) · no summary yetArvind Neelakantan et al.2015 · 274 citations
28. Modelling Relational Data using Bayesian Clustered Tensor Factorization ↗no summary yetIlya Sutskever, Ruslan Salakhutdinov, Joshua B. Tenenbaum2009 · 255 citations
29. Generative Language Modeling for Automated Theorem ProvingarXiv:2009.03393Stanislas Polu, Ilya Sutskever2020 · 241 citations
30. Consistency Models ↗arXiv (Cornell University) · no summary yetYang Song et al.2023 · 235 citations
31. One-Shot Imitation Learning ↗neural information processing systems · no summary yetYan Duan et al.2017 · 235 citations
32. Improving Variational Inference with Inverse Autoregressive Flow ↗arXiv (Cornell University) · no summary yetDiederik P. Kingma et al.2016 · 203 citations
33. Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak SupervisionarXiv:2312.09390Collin Burns, Pavel Izmailov, Jan Hendrik Kirchner, et al.2023 · 172 citations
34. Jukebox: A Generative Model for Music ↗arXiv (Cornell University) · no summary yetPrafulla Dhariwal et al.2020 · 165 citations
35. Scaling and evaluating sparse autoencoders ↗arXiv:2406.04093 · no summary yetLeo Gao et al.2024 · 163 citations
36. Neural Programmer: Inducing Latent Programs with Gradient Descent ↗arXiv:1511.04834 · no summary yetArvind Neelakantan, Quoc V. Le, Ilya Sutskever2015 · 142 citations
37. Reinforcement Learning Neural Turing Machines - Revised ↗arXiv:1505.00521 · no summary yetWojciech Zaremba, Ilya Sutskever2015 · 139 citations
38. Formal Mathematics Statement Curriculum LearningarXiv:2202.01344Stanislas Polu, Jesse Michael Han, Kunhao Zheng, et al.2022 · 133 citations
39. GamePad: A Learning Environment for Theorem Proving ↗arXiv:1806.00608 · no summary yetDaniel Huang et al.2018 · 94 citations
40. Neural Random-Access Machines ↗arXiv:1511.06392 · no summary yetKarol Kurach, Marcin Andrychowicz, Ilya Sutskever2015 · 50 citations
41. An Online Sequence-to-Sequence Model Using Partial Conditioning ↗arXiv (Cornell University) · no summary yetNavdeep Jaitly et al.2015 · 49 citations
42. Distribution Augmentation for Generative Modeling ↗International Conference on Machine Learning · no summary yetHeewoo Jun et al.2020 · 30 citations
43. Stochastic k-Neighborhood Selection for Supervised and Unsupervised Learning ↗no summary yetDaniel Tarlow et al.2013 · 30 citations
44. Unsupervised Neural Machine Translation with Generative Language Models Only ↗arXiv (Cornell University) · no summary yetJesse Michael Han et al.2021 · 22 citations
45. Towards Principled Unsupervised Learning ↗arXiv (Cornell University) · no summary yetIlya Sutskever et al.2015 · 21 citations
46. Extensions and Limitations of the Neural GPU ↗arXiv:1611.00736 · no summary yetEric Price, Wojciech Zaremba, Ilya Sutskever2016 · 16 citations
47. Conditional Augmentation for Generative Modeling ↗International Conference on Machine Learning · no summary yetHeewoo Jun et al.2020
48. tributed Representations of Words and Phrases and their Compositionality ” by ↗no summary yetYoav Goldberg et al.2014
49. 1 2 3 ↗no summary yetKevin Swersky et al.2013

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