| ABC: A Big CAD Model Dataset For Geometric Deep Learning S Koch, A Matveev, Z Jiang, F Williams, A Artemov, E Burnaev, M Alexa, ... Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019 | 196 | 2019 |
| Reinforcement learning for combinatorial optimization: A survey N Mazyavkina, S Sviridov, S Ivanov, E Burnaev Computers & Operations Research 134, 105400, 2021 | 156 | 2021 |
| Anonymous Walk Embeddings S Ivanov, E Burnaev ICML Proceedings; arXiv preprint arXiv:1805.11921, 2018 | 147 | 2018 |
| Steganographic generative adversarial networks D Volkhonskiy, I Nazarov, E Burnaev 12th Int. Conf. on Machine Vision (ICMV 2019) 11433, 114333M, 2020 | 133 | 2020 |
| Driving digital rock towards machine learning: predicting permeability with gradient boosting and deep neural networks O Sudakov, E Burnaev, D Koroteev Computers & geosciences 127, 91-98, 2019 | 131 | 2019 |
| Influence of resampling on accuracy of imbalanced classification E Burnaev, P Erofeev, A Papanov Eighth International Conference on Machine Vision, 987521-987521-5, 2015 | 86 | 2015 |
| One-class SVM with privileged information and its application to malware detection E Burnaev, D Smolyakov Data Mining Workshops (ICDMW), 2016 IEEE 16th International Conference on …, 2016 | 64 | 2016 |
| A predictive model for steady-state multiphase pipe flow: Machine learning on lab data EA Kanin, AA Osiptsov, AL Vainshtein, EV Burnaev Journal of Petroleum Science and Engineering 180, 727-746, 2019 | 59 | 2019 |
| GTApprox: surrogate modeling for industrial design M Belyaev, E Burnaev, E Kapushev, M Panov, P Prikhodko, D Vetrov, ... Advances in Engineering Software 102, 29-39, 2016 | 57 | 2016 |
| Conformal -NN Anomaly Detector for Univariate Data Streams V Ishimtsev, A Bernstein, E Burnaev, I Nazarov Conformal and Probabilistic Prediction and Applications, 213-227, 2017 | 50 | 2017 |
| Efficiency of conformalized ridge regression E Burnaev, V Vovk Conference on Learning Theory, 605-622, 2014 | 48 | 2014 |
| Adaptive design of experiments based on gaussian processes E Burnaev, M Panov International Symposium on Statistical Learning and Data Sciences, 116-125, 2015 | 47 | 2015 |
| Deep neural networks predicting oil movement in a development unit P Temirchev, M Simonov, R Kostoev, E Burnaev, I Oseledets, A Akhmetov, ... Journal of Petroleum Science and Engineering 184, 106513, 2020 | 46 | 2020 |
| Deep neural networks predicting oil movement in a development unit P Temirchev, M Simonov, R Kostoev, E Burnaev, I Oseledets, A Akhmetov, ... Journal of Petroleum Science and Engineering 184, 106513, 2020 | 46 | 2020 |
| Boundary Loss for Remote Sensing Imagery Semantic Segmentation A Bokhovkin, E Burnaev International Symposium on Neural Networks, 388-401, 2019 | 45 | 2019 |
| NAS-Bench-NLP: neural architecture search benchmark for natural language processing N Klyuchnikov, I Trofimov, E Artemova, M Salnikov, M Fedorov, A Filippov, ... IEEE Access 10, 45736-45747, 2022 | 43 | 2022 |
| Esports Athletes and Players: a Comparative Study N Khromov, A Korotin, A Lange, A Stepanov, E Burnaev, A Somov IEEE Pervasive Computing 18 (3), 31-39, 2019 | 41 | 2019 |
| Quadrature-based features for kernel approximation M Munkhoeva, Y Kapushev, E Burnaev, I Oseledets Advances in Neural Information Processing Systems 31, 2018 | 40 | 2018 |
| Quadrature-based features for kernel approximation M Munkhoeva, Y Kapushev, E Burnaev, I Oseledets Advances in neural information processing systems 31, 9147-9156, 2018 | 40 | 2018 |
| Efficient design of experiments for sensitivity analysis based on polynomial chaos expansions E Burnaev, I Panin, B Sudret Annals of Mathematics and Artificial Intelligence, 1-21, 2017 | 40 | 2017 |
Denis ZorinProfessor of Computer Science and Mathematics, Courant Institute, NYUVerified email at cs.nyu.edu
