| Tensorizing neural networks A Novikov, D Podoprikhin, A Osokin, D Vetrov Advances in Neural Information Processing Systems, 442-450, 2015 | 644 | 2015 |
| Ultimate tensorization: compressing convolutional and FC layers alike T Garipov, D Podoprikhin, A Novikov, D Vetrov arXiv preprint arXiv:1611.03214, 2016 | 127 | 2016 |
| Exponential machines A Novikov, M Trofimov, I Oseledets Bulletin of the Polish Academy of Sciences: Technical Sciences 6, 2018 | 93 | 2018 |
| Expressive power of recurrent neural networks V Khrulkov, A Novikov, I Oseledets International Conference on Learning Representations (ICLR), 2018 | 90 | 2018 |
| Acme: A Research Framework for Distributed Reinforcement Learning M Hoffman, B Shahriari, J Aslanides, G Barth-Maron, F Behbahani, ... arXiv preprint arXiv:2006.00979, 2020 | 80 | 2020 |
| Critic Regularized Regression Z Wang, A Novikov, K Żołna, JT Springenberg, S Reed, B Shahriari, ... Conference on Neural Information Processing Systems (NeurIPS), 2020 | 60 | 2020 |
| RL Unplugged: A Collection 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, 2020 | 55* | 2020 |
| 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 | 42 | 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 | 40* | 2020 |
| Putting MRFs on a tensor train A Novikov, A Rodomanov, A Osokin, D Vetrov International Conference on Machine Learning, 811-819, 2014 | 38 | 2014 |
| 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 | 36 | 2018 |
| 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 | 34 | 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 | 22 | 2020 |
| 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 | 13 | 2021 |
| 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 | 13 | 2020 |
| Low-rank Riemannian eigensolver for high-dimensional Hamiltonians M Rakhuba, A Novikov, I Oseledets Journal of Computational Physics, 2019 | 11 | 2019 |
| TFFM: Tensorflow implementation of an arbitrary order factorization machine M Trofimov, A Novikov | 10 | 2016 |
| 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 | 5 | 2020 |
| Visual Imitation with a Minimal Adversary S Reed, Y Aytar, Z Wang, T Paine, A van den Oord, T Pfaff, S Gomez, ... | 2 | 2018 |
| Automatic differentiation for Riemannian optimization on low-rank matrix and tensor-train manifolds A Novikov, M Rakhuba, I Oseledets arXiv preprint arXiv:2103.14974, 2021 | | 2021 |
Ziyu WangDeepmindVerified email at google.com
