| Highly accurate protein structure prediction with AlphaFold J Jumper, R Evans, A Pritzel, T Green, M Figurnov, O Ronneberger, ... Nature 596 (7873), 583-589, 2021 | 5433 | 2021 |
| Highly accurate protein structure prediction for the human proteome K Tunyasuvunakool, J Adler, Z Wu, T Green, M Zielinski, A Žídek, ... Nature 596 (7873), 590-596, 2021 | 760 | 2021 |
| AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models M Varadi, S Anyango, M Deshpande, S Nair, C Natassia, G Yordanova, ... Nucleic acids research 50 (D1), D439-D444, 2022 | 612 | 2022 |
| Spatially adaptive computation time for residual networks M Figurnov, MD Collins, Y Zhu, L Zhang, J Huang, D Vetrov, ... Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 287 | 2017 |
| Monte Carlo Gradient Estimation in Machine Learning. S Mohamed, M Rosca, M Figurnov, A Mnih J. Mach. Learn. Res. 21 (132), 1-62, 2020 | 223 | 2020 |
| Implicit reparameterization gradients M Figurnov, S Mohamed, A Mnih NeurIPS 2018, 2018 | 177 | 2018 |
| Perforatedcnns: Acceleration through elimination of redundant convolutions M Figurnov, A Ibraimova, DP Vetrov, P Kohli Advances in neural information processing systems 29, 2016 | 164 | 2016 |
| High accuracy protein structure prediction using deep learning J Jumper, R Evans, A Pritzel, T Green, M Figurnov, K Tunyasuvunakool, ... Fourteenth Critical Assessment of Techniques for Protein Structure …, 2020 | 113 | 2020 |
| Variational autoencoder with arbitrary conditioning O Ivanov, M Figurnov, D Vetrov ICLR 2019, 2018 | 107 | 2018 |
| Applying and improving AlphaFold at CASP14 J Jumper, R Evans, A Pritzel, T Green, M Figurnov, O Ronneberger, ... Proteins: Structure, Function, and Bioinformatics 89 (12), 1711-1721, 2021 | 74 | 2021 |
| Computational predictions of protein structures associated with COVID-19 J Jumper, K Tunyasuvunakool, P Kohli, D Hassabis, A Team DeepMind website, 2020 | 66* | 2020 |
| Tensor Train Decomposition on TensorFlow (T3F). A Novikov, P Izmailov, V Khrulkov, M Figurnov, IV Oseledets J. Mach. Learn. Res. 21 (30), 1-7, 2020 | 44 | 2020 |
| AlphaFold 2 J Jumper, R Evans, A Pritzel, T Green, M Figurnov, K Tunyasuvunakool, ... In Fourteenth Critical Assessment of Techniques for Protein Structure …, 2020 | 6 | 2020 |
| Probabilistic adaptive computation time M Figurnov, A Sobolev, D Vetrov arXiv preprint arXiv:1712.00386, 2017 | 6 | 2017 |
| Linear combination of random forests for the Relevance Prediction Challenge M Figurnov, A Kirillov Proc. of Int. Conf. on Web Service and Data Mining workshop on Web Search …, 2012 | 6 | 2012 |
| Measure-valued derivatives for approximate bayesian inference M Rosca, M Figurnov, S Mohamed, A Mnih NeurIPS Workshop on Approximate Bayesian Inference, 2019 | 4 | 2019 |
| Устойчивый к шуму метод обучения вариационного автокодировщика МВ Фигурнов, КА Струминский, ДП Ветров Интеллектуальные системы. Теория и приложения 21 (2), 90-109, 2017 | 2 | 2017 |
| Robust variational inference M Figurnov, K Struminsky, D Vetrov arXiv preprint arXiv:1611.09226, 2016 | 2 | 2016 |
| Protein Structure Prediction from Amino Acid Sequences Using Self-Attention Neural Networks J Jumper, AW Senior, RA Evans, RJ Bates, M Figurnov, A Pritzel, ... US Patent App. 17/108,890, 2021 | | 2021 |
| Entropy Estimates for Generative Models K Struminsky, M Figurnov, D Vetrov | | 2018 |
Dmitry VetrovHigher School of Economics, AI Research Institute, MoscowVerified email at hse.ru
