| Tensorflow: Large-scale machine learning on heterogeneous distributed systems M Abadi, A Agarwal, P Barham, E Brevdo, Z Chen, C Citro, GS Corrado, ... arXiv preprint arXiv:1603.04467, 2016 | 27556 | 2016 |
| Generating sentences from a continuous space SR Bowman, L Vilnis, O Vinyals, AM Dai, R Jozefowicz, S Bengio arXiv preprint arXiv:1511.06349, 2015 | 2470 | 2015 |
| An empirical exploration of recurrent network architectures R Jozefowicz, W Zaremba, I Sutskever | 2231 | 2015 |
| Improved variational inference with inverse autoregressive flow DP Kingma, T Salimans, R Jozefowicz, X Chen, I Sutskever, M Welling Advances in neural information processing systems 29, 2016 | 1810 | 2016 |
| Learning dexterous in-hand manipulation OAIM Andrychowicz, B Baker, M Chociej, R Jozefowicz, B McGrew, ... The International Journal of Robotics Research 39 (1), 3-20, 2020 | 1399 | 2020 |
| Dota 2 with large scale deep reinforcement learning C Berner, G Brockman, B Chan, V Cheung, P Dębiak, C Dennison, ... arXiv preprint arXiv:1912.06680, 2019 | 1374 | 2019 |
| Exploring the limits of language modeling R Jozefowicz, O Vinyals, M Schuster, N Shazeer, Y Wu arXiv preprint arXiv:1602.02410, 2016 | 1269 | 2016 |
| Revisiting distributed synchronous SGD J Chen, X Pan, R Monga, S Bengio, R Jozefowicz arXiv preprint arXiv:1604.00981, 2016 | 826 | 2016 |
| TensorFlow: Large-scale machine learning on heterogeneous systems, software available from tensorflow. org (2015) M Abadi, A Agarwal, P Barham, E Brevdo, Z Chen, C Citro, GS Corrado, ... URL https://www. tensorflow. org, 2015 | 696 | 2015 |
| Learning to generate reviews and discovering sentiment A Radford, R Jozefowicz, I Sutskever arXiv preprint arXiv:1704.01444, 2017 | 489 | 2017 |
| Inferring single-trial neural population dynamics using sequential auto-encoders C Pandarinath, DJ O’Shea, J Collins, R Jozefowicz, SD Stavisky, JC Kao, ... Nature methods 15 (10), 805-815, 2018 | 486 | 2018 |
| TensorFlow: large-scale machine learning on heterogeneous distributed systems. 2015 M Abadi, A Agarwal, P Barham, E Brevdo, Z Chen, C Citro, GS Corrado, ... URL http://download. tensorflow. org/paper/whitepaper2015. pdf, 12, 2015 | 355 | 2015 |
| TensorFlow: Large-scale machine learning on heterogeneous systems (2015), software available from tensorflow. org M Abadi, A Agarwal, P Barham, E Brevdo, Z Chen, C Citro, GS Corrado, ... URL https://www. tensorflow. org, 2019 | 247 | 2019 |
| Tensor ow: Large-scale machine learning on heterogeneous distributed systems M Abadi, A Agarwal, P Barham, E Brevdo, Z Chen, C Citro, GS Corrado, ... arXiv preprint arXiv:1603.04467 3, 2016 | 160 | 2016 |
| Dota 2 with large scale deep reinforcement learning CB OpenAI, G Brockman, B Chan, V Cheung, P Debiak, C Dennison, ... arXiv preprint arXiv:1912.06680 2, 2019 | 92 | 2019 |
| Lfads-latent factor analysis via dynamical systems D Sussillo, R Jozefowicz, LF Abbott, C Pandarinath arXiv preprint arXiv:1608.06315, 2016 | 81 | 2016 |
| Towards principled unsupervised learning I Sutskever, R Jozefowicz, K Gregor, D Rezende, T Lillicrap, O Vinyals arXiv preprint arXiv:1511.06440, 2015 | 66 | 2015 |
| Potential for optimizing the Higgs boson measurement in decays at the LHC including machine learning techniques R Józefowicz, E Richter-Was, Z Was Physical Review D 94 (9), 093001, 2016 | 31 | 2016 |
| TensorFlow: Large-scale machine learning on heterogeneous systems. tensorflow. org M Abadi, A Agarwal, P Barham, E Brevdo, Z Chen, C Citro, GS Corrado, ... Accessed May 24, 2020, 2015 | 30 | 2015 |
| i Xiaoqiang Zheng M Abadi, A Agarwal, P Barham, E Brevdo, Z Chen, C Citro, GS Corrado, ... TensorFlow: Large-scale machine learning on heterogeneous systems, 2015 | 29 | 2015 |
Ilya SutskeverCo-Founder and Chief Scientist of OpenAIVerified email at openai.com
