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Generative Language Modeling for Automated Theorem Proving

Sep 07, 2020
Stanislas Polu, Ilya Sutskever

* 15+5 pages 

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Language Models are Few-Shot Learners

Jun 05, 2020
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, Dario Amodei

* 40+32 pages 

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Jukebox: A Generative Model for Music

Apr 30, 2020
Prafulla Dhariwal, Heewoo Jun, Christine Payne, Jong Wook Kim, Alec Radford, Ilya Sutskever


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Dota 2 with Large Scale Deep Reinforcement Learning

Dec 13, 2019
OpenAI, :, Christopher Berner, Greg Brockman, Brooke Chan, Vicki Cheung, PrzemysŇāaw Dńôbiak, Christy Dennison, David Farhi, Quirin Fischer, Shariq Hashme, Chris Hesse, Rafal J√≥zefowicz, Scott Gray, Catherine Olsson, Jakub Pachocki, Michael Petrov, Henrique Pond√© de Oliveira Pinto, Jonathan Raiman, Tim Salimans, Jeremy Schlatter, Jonas Schneider, Szymon Sidor, Ilya Sutskever, Jie Tang, Filip Wolski, Susan Zhang


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Deep Double Descent: Where Bigger Models and More Data Hurt

Dec 04, 2019
Preetum Nakkiran, Gal Kaplun, Yamini Bansal, Tristan Yang, Boaz Barak, Ilya Sutskever

* G.K. and Y.B. contributed equally 

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Generating Long Sequences with Sparse Transformers

Apr 23, 2019
Rewon Child, Scott Gray, Alec Radford, Ilya Sutskever


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FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models

Oct 22, 2018
Will Grathwohl, Ricky T. Q. Chen, Jesse Bettencourt, Ilya Sutskever, David Duvenaud

* 8 Pages, 6 figures 

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GamePad: A Learning Environment for Theorem Proving

Jun 02, 2018
Daniel Huang, Prafulla Dhariwal, Dawn Song, Ilya Sutskever


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Emergent Complexity via Multi-Agent Competition

Mar 14, 2018
Trapit Bansal, Jakub Pachocki, Szymon Sidor, Ilya Sutskever, Igor Mordatch

* Published as a conference paper at ICLR 2018 

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Some Considerations on Learning to Explore via Meta-Reinforcement Learning

Mar 03, 2018
Bradly C. Stadie, Ge Yang, Rein Houthooft, Xi Chen, Yan Duan, Yuhuai Wu, Pieter Abbeel, Ilya Sutskever


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Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments

Feb 23, 2018
Maruan Al-Shedivat, Trapit Bansal, Yuri Burda, Ilya Sutskever, Igor Mordatch, Pieter Abbeel

* Published as a conference paper at ICLR 2018 

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One-Shot Imitation Learning

Dec 04, 2017
Yan Duan, Marcin Andrychowicz, Bradly C. Stadie, Jonathan Ho, Jonas Schneider, Ilya Sutskever, Pieter Abbeel, Wojciech Zaremba


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Evolution Strategies as a Scalable Alternative to Reinforcement Learning

Sep 07, 2017
Tim Salimans, Jonathan Ho, Xi Chen, Szymon Sidor, Ilya Sutskever


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An online sequence-to-sequence model for noisy speech recognition

Jun 16, 2017
Chung-Cheng Chiu, Dieterich Lawson, Yuping Luo, George Tucker, Kevin Swersky, Ilya Sutskever, Navdeep Jaitly

* arXiv admin note: substantial text overlap with arXiv:1608.01281 

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Learning to Generate Reviews and Discovering Sentiment

Apr 06, 2017
Alec Radford, Rafal Jozefowicz, Ilya Sutskever


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Third-Person Imitation Learning

Mar 06, 2017
Bradly C. Stadie, Pieter Abbeel, Ilya Sutskever


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Variational Lossy Autoencoder

Mar 04, 2017
Xi Chen, Diederik P. Kingma, Tim Salimans, Yan Duan, Prafulla Dhariwal, John Schulman, Ilya Sutskever, Pieter Abbeel

* Added CIFAR10 experiments; ICLR 2017 

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Improving Variational Inference with Inverse Autoregressive Flow

Jan 30, 2017
Diederik P. Kingma, Tim Salimans, Rafal Jozefowicz, Xi Chen, Ilya Sutskever, Max Welling


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RL$^2$: Fast Reinforcement Learning via Slow Reinforcement Learning

Nov 10, 2016
Yan Duan, John Schulman, Xi Chen, Peter L. Bartlett, Ilya Sutskever, Pieter Abbeel

* 14 pages. Under review as a conference paper at ICLR 2017 

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Extensions and Limitations of the Neural GPU

Nov 04, 2016
Eric Price, Wojciech Zaremba, Ilya Sutskever


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A Neural Transducer

Aug 04, 2016
Navdeep Jaitly, David Sussillo, Quoc V. Le, Oriol Vinyals, Ilya Sutskever, Samy Bengio


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Neural Programmer: Inducing Latent Programs with Gradient Descent

Aug 04, 2016
Arvind Neelakantan, Quoc V. Le, Ilya Sutskever

* Accepted as a conference paper at ICLR 2015 

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Learning Online Alignments with Continuous Rewards Policy Gradient

Aug 03, 2016
Yuping Luo, Chung-Cheng Chiu, Navdeep Jaitly, Ilya Sutskever


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InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets

Jun 12, 2016
Xi Chen, Yan Duan, Rein Houthooft, John Schulman, Ilya Sutskever, Pieter Abbeel


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TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

Mar 16, 2016
Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Jozefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dan Mane, Rajat Monga, Sherry Moore, Derek Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda Viegas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, Xiaoqiang Zheng

* Version 2 updates only the metadata, to correct the formatting of Mart\'in Abadi's name 

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Neural GPUs Learn Algorithms

Mar 15, 2016
ŇĀukasz Kaiser, Ilya Sutskever


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Continuous Deep Q-Learning with Model-based Acceleration

Mar 02, 2016
Shixiang Gu, Timothy Lillicrap, Ilya Sutskever, Sergey Levine


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Multi-task Sequence to Sequence Learning

Mar 01, 2016
Minh-Thang Luong, Quoc V. Le, Ilya Sutskever, Oriol Vinyals, Lukasz Kaiser

* 10 pages, 4 figures, ICLR 2016 camera-ready, added parsing SOTA results 

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