Tensorizing neural networks A Novikov, D Podoprikhin, A Osokin, D Vetrov Advances in Neural Information Processing Systems, 442-450, 2015 | 1035 | 2015 |
A Generalist Agent S Reed, K Zolna, E Parisotto, SG Colmenarejo, A Novikov, G Barth-Maron, ... arXiv preprint arXiv:2205.06175, 2022 | 830 | 2022 |
Discovering faster matrix multiplication algorithms with reinforcement learning A Fawzi, M Balog, A Huang, T Hubert, B Romera-Paredes, M Barekatain, ... Nature 610 (7930), 47-53, 2022 | 561 | 2022 |
Critic Regularized Regression Z Wang, A Novikov, K Żołna, JT Springenberg, S Reed, B Shahriari, ... Conference on Neural Information Processing Systems (NeurIPS), 2020 | 317 | 2020 |
Acme: A research framework for distributed reinforcement learning MW Hoffman, B Shahriari, J Aslanides, G Barth-Maron, N Momchev, ... arXiv preprint arXiv:2006.00979, 2020 | 251 | 2020 |
Ultimate tensorization: compressing convolutional and FC layers alike T Garipov, D Podoprikhin, A Novikov, D Vetrov arXiv preprint arXiv:1611.03214, 2016 | 233 | 2016 |
Mathematical discoveries from program search with large language models B Romera-Paredes, M Barekatain, A Novikov, M Balog, MP Kumar, ... Nature 625 (7995), 468-475, 2024 | 197 | 2024 |
Rl unplugged: A suite of benchmarks for offline reinforcement learning C Gulcehre, Z Wang, A Novikov, T Paine, S Gómez, K Zolna, R Agarwal, ... Advances in Neural Information Processing Systems 33, 7248-7259, 2020 | 195 | 2020 |
Scaling data-driven robotics with reward sketching and batch reinforcement learning S Cabi, SG Colmenarejo, A Novikov, K Konyushkova, S Reed, R Jeong, ... Robotics: Science and Systems (RSS), 2020 | 167* | 2020 |
Exponential machines A Novikov, M Trofimov, I Oseledets Bulletin of the Polish Academy of Sciences: Technical Sciences 6, 2018 | 159 | 2018 |
Hyperparameter Selection for Offline Reinforcement Learning TL Paine, C Paduraru, A Michi, C Gulcehre, K Zolna, A Novikov, Z Wang, ... arXiv preprint arXiv:2007.09055, 2020 | 155 | 2020 |
Expressive power of recurrent neural networks V Khrulkov, A Novikov, I Oseledets International Conference on Learning Representations (ICLR), 2018 | 130 | 2018 |
Benchmarks for Deep Off-Policy Evaluation J Fu, M Norouzi, O Nachum, G Tucker, Z Wang, A Novikov, M Yang, ... International Conference on Learning Representations (ICLR), 2021 | 89 | 2021 |
Scalable Gaussian Processes with Billions of Inducing Inputs via Tensor Train Decomposition P Izmailov, A Novikov, D Kropotov The 21st International Conference on Artificial Intelligence and Statistics …, 2018 | 73 | 2018 |
Offline learning from demonstrations and unlabeled experience K Zolna, A Novikov, K Konyushkova, C Gulcehre, Z Wang, Y Aytar, ... arXiv preprint arXiv:2011.13885, 2020 | 70 | 2020 |
Tensor Train decomposition on TensorFlow (T3F) A Novikov, P Izmailov, V Khrulkov, M Figurnov, I Oseledets Journal of Machine Learning Research, Machine Learning Open Source Software …, 2020 | 70 | 2020 |
Task-Relevant Adversarial Imitation Learning K Zolna, S Reed, A Novikov, SG Colmenarej, D Budden, S Cabi, M Denil, ... Conference on Robot Learning (CORL), 2020 | 62 | 2020 |
Putting MRFs on a tensor train A Novikov, A Rodomanov, A Osokin, D Vetrov International Conference on Machine Learning, 811-819, 2014 | 56 | 2014 |
Semi-supervised reward learning for offline reinforcement learning K Konyushkova, K Zolna, Y Aytar, A Novikov, S Reed, S Cabi, ... arXiv preprint arXiv:2012.06899, 2020 | 35 | 2020 |
Low-rank Riemannian eigensolver for high-dimensional Hamiltonians M Rakhuba, A Novikov, I Oseledets Journal of Computational Physics, 2019 | 14 | 2019 |