| A velocity-space adaptive unified gas kinetic scheme for continuum and rarefied flows T Xiao, C Liu, K Xu, Q Cai Journal of Computational Physics 415, 109535, 2020 | 33 | 2020 |
| A well-balanced unified gas-kinetic scheme for multiscale flow transport under gravitational field T Xiao, Q Cai, K Xu Journal of Computational Physics 332, 475-491, 2017 | 29 | 2017 |
| Using neural networks to accelerate the solution of the Boltzmann equation T Xiao, M Frank Journal of Computational Physics 443, 110521, 2021 | 27 | 2021 |
| An investigation of non-equilibrium heat transport in a gas system under external force field T Xiao, K Xu, Q Cai, T Qian International Journal of Heat and Mass Transfer 126, 362-379, 2018 | 23 | 2018 |
| A stochastic kinetic scheme for multi-scale plasma transport with uncertainty quantification T Xiao, M Frank Journal of Computational Physics 432, 110139, 2021 | 18 | 2021 |
| A unified gas-kinetic scheme for multiscale and multicomponent flow transport T Xiao, K Xu, Q Cai Applied Mathematics and Mechanics 40 (3), 355-372, 2019 | 17 | 2019 |
| A flux reconstruction kinetic scheme for the Boltzmann equation T Xiao Journal of Computational Physics 447, 110689, 2021 | 16 | 2021 |
| Kinetic. jl: A portable finite volume toolbox for scientific and neural computing T Xiao Journal of Open Source Software 6 (62), 3060, 2021 | 14 | 2021 |
| Structure Preserving Neural Networks: A Case Study in the Entropy Closure of the Boltzmann Equation. S Schotthöfer, T Xiao, M Frank, CD Hauck ICML, 19406-19433, 2022 | 10 | 2022 |
| A stochastic kinetic scheme for multi-scale flow transport with uncertainty quantification T Xiao, M Frank Journal of Computational Physics 437, 110337, 2021 | 9 | 2021 |
| Neural network-based, structure-preserving entropy closures for the Boltzmann moment system S Schotthöfer, T Xiao, M Frank, CD Hauck arXiv preprint arXiv:2201.10364, 2022 | 8 | 2022 |
| A structure-preserving surrogate model for the closure of the moment system of the Boltzmann equation using convex deep neural networks S Schotthöfer, T Xiao, M Frank, C Hauck AIAA Aviation 2021 Forum, 2895, 2021 | 7 | 2021 |
| RelaxNet: A structure-preserving neural network to approximate the Boltzmann collision operator T Xiao, M Frank Journal of Computational Physics 490, 112317, 2023 | 6 | 2023 |
| 有机硫恶臭气体治理方法的研究进展 张帆， 王祖武， 吴晓璇， 周思宇， 蒋遥， 肖天白， 向秀华 湖北理工学院学报 29 (4), 24-27, 2013 | 5 | 2013 |
| KiT-RT: An extendable framework for radiative transfer and therapy J Kusch, S Schotthöfer, P Stammer, J Wolters, T Xiao ACM Transactions on Mathematical Software 49 (4), 1-24, 2023 | 3 | 2023 |
| Predicting continuum breakdown with deep neural networks T Xiao, S Schotthöfer, M Frank Journal of Computational Physics 489, 112278, 2023 | 3 | 2023 |
| A Well-Balanced Unified Gas-Kinetic Scheme for Multicomponent Flows under External Force Field T Xiao Entropy 24 (8), 1110, 2022 | 2 | 2022 |
| A flux reconstruction stochastic Galerkin scheme for hyperbolic conservation laws T Xiao, J Kusch, J Koellermeier, M Frank Journal of Scientific Computing 95 (1), 18, 2023 | 1 | 2023 |
| Artificial intelligence and machine learning in aerodynamics J Kou, T Xiao Metascience in Aerospace 1 (2), 190-218, 2024 | | 2024 |
| Structure-Preserving Operator Learning: Modeling the Collision Operator of Kinetic Equations JY Lee, S Schotthöfer, T Xiao, S Krumscheid, M Frank arXiv preprint arXiv:2402.16613, 2024 | | 2024 |
Martin FrankComputational Science & Mathematical Methods, Steinbuch Center for Computing, Karlsruhe Institute of Technology在 kit.edu 的电子邮件经过验证
