| 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 | 17023 | 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 | 3207 | 2022 |
| 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 | 1715 | 2021 |
| Monte carlo gradient estimation in machine learning S Mohamed, M Rosca, M Figurnov, A Mnih The Journal of Machine Learning Research 21 (1), 5183-5244, 2020 | 371 | 2020 |
| 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 | 359 | 2017 |
| Implicit reparameterization gradients M Figurnov, S Mohamed, A Mnih NeurIPS 2018, 2018 | 238 | 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 | 214 | 2021 |
| Perforatedcnns: Acceleration through elimination of redundant convolutions M Figurnov, A Ibraimova, DP Vetrov, P Kohli Advances in neural information processing systems 29, 2016 | 184 | 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 | 143 | 2020 |
| Variational autoencoder with arbitrary conditioning O Ivanov, M Figurnov, D Vetrov ICLR 2019, 2018 | 142 | 2018 |
| Computational predictions of protein structures associated with COVID-19 J Jumper, K Tunyasuvunakool, P Kohli, D Hassabis, A Team DeepMind website 6, 2020 | 74* | 2020 |
| Tensor train decomposition on tensorflow (t3f) A Novikov, P Izmailov, V Khrulkov, M Figurnov, I Oseledets The Journal of Machine Learning Research 21 (1), 1105-1111, 2020 | 61 | 2020 |
| AlphaFold 2 J Jumper, R Evans, A Pritzel, T Green, M Figurnov, K Tunyasuvunakool, ... Fourteenth Critical Assessment of Techniques for Protein Structure …, 2020 | 17 | 2020 |
| Probabilistic adaptive computation time M Figurnov, A Sobolev, D Vetrov arXiv preprint arXiv:1712.00386, 2017 | 8 | 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 |
| Predicting protein structures by sharing information between multiple sequence alignments and pair embeddings M Figurnov, A Pritzel, RA Evans, RJ Bates, O Ronneberger, S Kohl, ... US Patent App. 18/026,376, 2023 | | 2023 |
| 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 |
Dmitry VetrovProfessor of Computer Science at Constructor University, BremenVerified email at constructor.university
