Publications of Y. Yudin
All genres
Conference Paper (2)
1.
Conference Paper
Epistemic and Aleatoric Uncertainty Quantification and Surrogate Modelling in High-Performance Multiscale Plasma Physics Simulations. In: Computational Science – ICCS 2023, pp. 572 - 586 (Eds. Mikyska, J.; Mulatier, C. v.; Paszynski, M.; Krzhizhanovskaya, V. V.; Dongarra, J. J. et al.). 23rd International Conference on Computational Science (ICCS 2023), Prague, July 03, 2023 - July 05, 2023. Springer, Cham (2023)
2.
Conference Paper
Performing Validation, Verification, and Sensitivity Analysis on Multiscale Fusion Plasma Simulations with the VECMA Toolkit. In: 47th EPS Conference on Plasma Physics, P2.1075 (Eds. Giruzzi, G.; Arnas, C.; Borba, D.; Gopla, A.; Lebedev, S. et al.). 47th EPS Conference on Plasma Physics, Virtual, June 21, 2021 - June 25, 2021. European Physical Society, Geneva (2021)
Poster (4)
3.
Poster
Uncertainty Quantification for Multiscale Turbulent Transport Simulations. 86. Jahrestagung der DPG und DPG-Frühjahrstagung der Sektion Materie und Kosmos (SMuK), Dresden (submitted)
4.
Poster
Performing Validation, Verification, and Sensitivity Analysis on Multiscale Fusion Plasma Simulations with the VECMA Toolkit. 47th EPS Conference on Plasma Physics, Virtual (2021)
5.
Poster
Gaussian Process Surrogate Models for Uncertainty Quantification in Multiscale Turbulent Transport Simulations. DPG-Tagung der Sektion Materie und Kosmos (SMuK), Virtual (submitted)
6.
Poster
Uncertainty Quantification for Multiscale Turbulent Transport Simulations. DPG-Frühjahrstagung der Fachverbände Physik der Hadronen und Kerne, Plasmaphysik und des Arbeitskreises Beschleunigerphysik
, Mainz, Virtual (submitted)
Thesis - PhD (1)
7.
Thesis - PhD
Uncertainty Quantification and Machine Learning Surrogate Models for Multi-Scale High-Performance-Computing Plasma Physics Turbulent Transport Simulations. Dissertation, 140 pp., TUM School of Computation, Information and Technology, Technische Universität München, München (2024)
Report (1)
8.
Report
Uncertainty Quantification and Machine Learning Surrogate Models for Multi-Scale High-Performance-Computing Plasma Physics Turbulent Simulations. Max-Planck-Institut für Plasmaphysik, Garching (2024), 128 pp.