| Grandmaster level in StarCraft II using multi-agent reinforcement learning O Vinyals, I Babuschkin, WM Czarnecki, M Mathieu, A Dudzik, J Chung, ... nature 575 (7782), 350-354, 2019 | 5074 | 2019 |
| Starcraft ii: A new challenge for reinforcement learning O Vinyals, T Ewalds, S Bartunov, P Georgiev, AS Vezhnevets, M Yeo, ... arXiv preprint arXiv:1708.04782, 2017 | 1143 | 2017 |
| FeUdal Networks for Hierarchical Reinforcement Learning AS Vezhnevets, S Osindero, T Schaul, N Heess, M Jaderberg, D Silver, ... ICML, 2017 | 1136 | 2017 |
| Modest adaboost: teaching AdaBoost to generalize better. A Vezhnevets, V Vezhnevets GraphiCon, 2005 | 324 | 2005 |
| Towards weakly supervised semantic segmentation by means of multiple instance and multitask learning A Vezhnevets, JM Buhmann Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on …, 2010 | 201 | 2010 |
| Weakly Supervised Structured Output Learning for Semantic Segmentation A Vezhnevets, V Ferrari, JM Buhmann Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on, 2012 | 200 | 2012 |
| Weakly Supervised Semantic Segmentation with a Multi-image Model A Vezhnevets, V Ferrari, J Buhmann Computer Vision (ICCV), 2011 IEEE International Conference on, 3249-3256, 2011 | 194 | 2011 |
| Strategic Attentive Writer for Learning Macro-Actions A Vezhnevets, V Mnih, J Agapiou, S Osindero, A Graves, O Vinyals, ... arXiv preprint arXiv:1606.04695, 2016 | 185 | 2016 |
| Active Learning for Semantic Segmentation with Expected Change A Vezhnevets, JM Buhmann, V Ferrari Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on, 2012 | 170 | 2012 |
| Avoiding boosting overfitting by removing confusing samples A Vezhnevets, O Barinova Machine Learning: ECML 2007, 430-441, 2007 | 128 | 2007 |
| Scalable evaluation of multi-agent reinforcement learning with melting pot A Vezhnevets, JZ Leibo, EA Dueñez-Guzman, JP Agapiou, P Sunehag, ... International conference on machine learning, 6187-6199, 2021 | 102 | 2021 |
| An active search strategy for efficient object class detection A Gonzalez-Garcia, A Vezhnevets, V Ferrari Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 85 | 2015 |
| Options as responses: Grounding behavioural hierarchies in multi-agent reinforcement learning A Vezhnevets, Y Wu, M Eckstein, R Leblond, JZ Leibo International Conference on Machine Learning, 9733-9742, 2020 | 59 | 2020 |
| GML AdaBoostMatlab Toolbox Manual A Vezhnevets, V Vezhnevets Moscow: MSU Graphics & Media Lab, 2010 | 55* | 2010 |
| A learning agent that acquires social norms from public sanctions in decentralized multi-agent settings E Vinitsky, R Köster, JP Agapiou, EA Duéñez-Guzmán, AS Vezhnevets, ... Collective Intelligence 2 (2), 26339137231162025, 2023 | 46 | 2023 |
| Anisotropic ssTEM Image Segmentation Using Dense Correspondence across Sections D Laptev, A Vezhnevets, S Dwivedi, JM Buhmann Medical Image Computing and Computer Assisted Intervention (MICCAI), 2012 | 40 | 2012 |
| Melting Pot 2.0 JP Agapiou, AS Vezhnevets, EA Duéñez-Guzmán, J Matyas, Y Mao, ... arXiv preprint arXiv:2211.13746, 2022 | 37 | 2022 |
| Weakly Supervised Semantic Segmentation of Crohn's Disease Tissues from Abnominal MRI D Mahapatra, A Vezhnevets, PJ Schuffler, JAW Tielbeek, FM Vos, ... International Symposium on Biomedical Imaging, 2013 | 35 | 2013 |
| Generative agent-based modeling with actions grounded in physical, social, or digital space using Concordia AS Vezhnevets, JP Agapiou, A Aharon, R Ziv, J Matyas, ... arXiv preprint arXiv:2312.03664, 2023 | 28 | 2023 |
| Associative embeddings for large-scale knowledge transfer with self-assessment A Vezhnevets, V Ferrari Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on, 2014 | 24 | 2014 |
John P AgapiouStaff Research Engineer, Google DeepMind在 google.com 的电子邮件经过验证