Reinforcement learning for combinatorial optimization: A survey N Mazyavkina, S Sviridov, S Ivanov, E Burnaev Computers & Operations Research 134, 105400, 2021 | 559 | 2021 |
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 | 435 | 2019 |
Steganographic generative adversarial networks D Volkhonskiy, I Nazarov, E Burnaev 12th Int. Conf. on Machine Vision (ICMV 2019) 11433, 114333M, 2020 | 230 | 2020 |
Anonymous Walk Embeddings S Ivanov, E Burnaev ICML Proceedings; arXiv preprint arXiv:1805.11921, 2018 | 212 | 2018 |
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 | 202 | 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 | 114 | 2015 |
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 | 113 | 2022 |
Latent Video Transformer R Rakhimov, D Volkhonskiy, A Artemov, D Zorin, E Burnaev arXiv preprint arXiv:2006.10704, 2020 | 112 | 2020 |
Boundary loss for remote sensing imagery semantic segmentation A Bokhovkin, E Burnaev Advances in Neural Networks–ISNN 2019: 16th International Symposium on …, 2019 | 107 | 2019 |
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 | 100 | 2019 |
Wasserstein-2 Generative Networks A Korotin, V Egiazarian, A Asadulaev, A Safin, E Burnaev arXiv preprint arXiv:1909.13082, 2019 | 94 | 2019 |
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 | 93 | 2016 |
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 | 72 | 2019 |
Data-driven model for the identification of the rock type at a drilling bit N Klyuchnikov, A Zaytsev, A Gruzdev, G Ovchinnikov, K Antipova, ... Journal of Petroleum science and Engineering 178, 506-516, 2019 | 70 | 2019 |
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 | 70 | 2017 |
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 | 69 | 2016 |
Do neural optimal transport solvers work? a continuous wasserstein-2 benchmark A Korotin, L Li, A Genevay, JM Solomon, A Filippov, E Burnaev Advances in Neural Information Processing Systems 34, 14593-14605, 2021 | 66 | 2021 |
Large-scale wasserstein gradient flows P Mokrov, A Korotin, L Li, A Genevay, JM Solomon, E Burnaev Advances in Neural Information Processing Systems 34, 15243-15256, 2021 | 66 | 2021 |
Monocular 3D Object Detection via Geometric Reasoning on Keypoints I Barabanau, A Artemov, E Burnaev, V Murashkin arXiv preprint arXiv:1905.05618, 2019 | 66 | 2019 |
Data-driven model for fracturing design optimization: focus on building digital database and production forecast AD Morozov, DO Popkov, VM Duplyakov, RF Mutalova, AA Osiptsov, ... arXiv, arXiv: 1910.14499, 2019 | 64* | 2019 |