Are generative deep models for novelty detection truly better? V Škvára, T Pevný, V Šmídl arXiv preprint arXiv:1807.05027, 2018 | 47 | 2018 |
Overview of the COMPASS results M Hron, J Adamek, J Cavalier, R Dejarnac, O Ficker, O Grover, J Horáček, ... Nuclear Fusion 62 (4), 042021, 2022 | 14 | 2022 |
Detection of Alfvén eigenmodes on COMPASS with generative neural networks V Škvára, V Šmídl, T Pevný, J Seidl, A Havránek, D Tskhakaya Fusion Science and Technology 76 (8), 962-971, 2020 | 12 | 2020 |
Comparison of anomaly detectors: Context matters V Škvára, J Francå, M Zorek, T Pevný, V Šmídl IEEE Transactions on Neural Networks and Learning Systems 33 (6), 2494-2507, 2021 | 9 | 2021 |
Robust sparse linear regression for tokamak plasma boundary estimation using variational Bayes V Škvára, V Šmídl, J Urban Journal of Physics: Conference Series 1047 (1), 012015, 2018 | 2 | 2018 |
Is AUC the best measure for practical comparison of anomaly detectors? V Škvára, T Pevný, V Šmídl arXiv preprint arXiv:2305.04754, 2023 | 1 | 2023 |
On-line Model Structure Selection for Estimation of Plasma Boundary in a Tokamak V Škvára, V Šmídl, J Urban Journal of Physics: Conference Series 659 (1), 012010, 2015 | 1 | 2015 |
Semi-supervised deep networks for plasma state identification M Zorek, V Škvára, V Šmídl, T Pevný, J Seidl, O Grover, Compass Team Plasma Physics and Controlled Fusion 64 (12), 125004, 2022 | | 2022 |
On-line Model Structure Selection for Estimation of Plasma Boundary in a Tokamak Š Vít, Š Václav, U Jakub Journal of Physics: Conference Series, 12th European Workshop on Advanced …, 0 | | |