| Multiagent cooperation and competition with deep reinforcement learning A Tampuu, T Matiisen, D Kodelja, I Kuzovkin, K Korjus, J Aru, J Aru, ... PloS one 12 (4), e0172395, 2017 | 1108 | 2017 |
| Activations of deep convolutional neural networks are aligned with gamma band activity of human visual cortex I Kuzovkin, R Vicente, M Petton, JP Lachaux, M Baciu, P Kahane, ... Communications biology 1 (1), 107, 2018 | 120 | 2018 |
| Combining static and dynamic features for multivariate sequence classification A Leontjeva, I Kuzovkin 2016 IEEE International Conference on Data Science and Advanced Analytics …, 2016 | 56 | 2016 |
| Addressing sample complexity in visual tasks using her and hallucinatory gans H Sahni, T Buckley, P Abbeel, I Kuzovkin Advances in Neural Information Processing Systems 32, 2019 | 19* | 2019 |
| Offworld gym: open-access physical robotics environment for real-world reinforcement learning benchmark and research A Kumar, T Buckley, JB Lanier, Q Wang, A Kavelaars, I Kuzovkin arXiv preprint arXiv:1910.08639, 2019 | 13 | 2019 |
| Direct information transfer rate optimisation for SSVEP-based BCI A Ingel, I Kuzovkin, R Vicente Journal of neural engineering 16 (1), 016016, 2018 | 12 | 2018 |
| Mental state space visualization for interactive modeling of personalized BCI control strategies I Kuzovkin, K Tretyakov, A Uusberg, R Vicente Journal of Neural Engineering 17 (1), 016059, 2020 | 11 | 2020 |
| Pattern recognition for non-invasive EEG-based BCI I Kuzovkin University of Tartu (http://kt. era. ee/supervision/Kuzovkin2011. pdf), 2011 | 6 | 2011 |
| Identifying task-relevant spectral signatures of perceptual categorization in the human cortex I Kuzovkin, JR Vidal, M Perrone-Bertolotti, P Kahane, S Rheims, J Aru, ... Scientific reports 10 (1), 7870, 2020 | 5* | 2020 |
| Adaptive Interactive Learning: a Novel Approach to Training Brain-Computer Interface Systems I Kuzovkin Master’s Thesis, 25, 2013 | 3 | 2013 |
| Offline Robot Reinforcement Learning with Uncertainty-Guided Human Expert Sampling A Kumar, I Kuzovkin arXiv preprint arXiv:2212.08232, 2022 | 2 | 2022 |
| Understanding information processing in human brain by interpreting machine learning models I Kuzovkin arXiv preprint arXiv:2010.08715, 2020 | 2 | 2020 |
| Empirical comparison of machine learning algorithms based on EEG data I Kuzovkin, K Korjus Bachelor’s esis, 2016 | 2 | 2016 |
| Replicating the Paper “Playing Atari with Deep Reinforcement Learning.” K Korjus, I Kuzovkin, A Tampuu, T Pungas Technical Report, Introduction to Computational Neuroscience, University of …, 2013 | 2 | 2013 |
| OffWorld Gym: open-access physical lunar analog environment for reinforcement learning and robotics research I Kuzovkin, J Lanier, A Kumar, Q Wang 43rd COSPAR Scientific Assembly. Held 28 January-4 February 43, 164, 2021 | | 2021 |
| Signal Quality and Data Visualizer for Emotiv EPOC U Loskit, I Kuzovkin | | 2014 |
| Interaktiivne kohandamisvõimeline õppimine: uus lähenemine aju-arvuti liidese süsteemi õpetamiseks I Kuzovkin Tartu Ülikool, 2013 | | 2013 |
| Mustride tuvastamine mitteinvasiivse EEG tehnoloogial baseeruvas Aju-Arvuti liideses I Kuzovkin Tartu Ülikool, 2011 | | 2011 |
| Noise Reduction on the Raw Signal of Emotiv EEG Neuroheadset RH Tunnel, I Kuzovkin | | |
| Framework for Training BCI System I Kuzovkin | | |
Raul VicenteProfessor of Data Science, Institute of Computer Science, University of Tartu在 ut.ee 的电子邮件经过验证