| Machine learning in cardiovascular flows modeling: Predicting arterial blood pressure from non-invasive 4D flow MRI data using physics-informed neural networks G Kissas, Y Yang, E Hwuang, WR Witschey, JA Detre, P Perdikaris Computer Methods in Applied Mechanics and Engineering 358, 112623, 2020 | 576 | 2020 |
| Adversarial uncertainty quantification in physics-informed neural networks Y Yang, P Perdikaris Journal of Computational Physics 394, 136-152, 2019 | 441 | 2019 |
| Physics-informed neural networks for cardiac activation mapping F Sahli Costabal, Y Yang, P Perdikaris, DE Hurtado, E Kuhl Frontiers in Physics 8, 42, 2020 | 394 | 2020 |
| Conditional deep surrogate models for stochastic, high-dimensional, and multi-fidelity systems Y Yang, P Perdikaris Computational Mechanics 64, 417-434, 2019 | 73 | 2019 |
| Physics-informed deep generative models Y Yang, P Perdikaris Third workshop on Bayesian Deep Learning (NeurIPS 2018), Montréal, Canada, 2018 | 62 | 2018 |
| Bayesian differential programming for robust systems identification under uncertainty Y Yang, M Aziz Bhouri, P Perdikaris Proceedings of the Royal Society A 476 (2243), 20200290, 2020 | 51 | 2020 |
| Scalable uncertainty quantification for deep operator networks using randomized priors Y Yang, G Kissas, P Perdikaris Computer Methods in Applied Mechanics and Engineering 399, 115399, 2022 | 47 | 2022 |
| Accurate artificial boundary conditions for the semi-discretized linear Schrödinger and heat equations on rectangular domains S Ji, Y Yang, G Pang, X Antoine Computer Physics Communications 222, 84-93, 2018 | 32 | 2018 |
| Output-weighted sampling for multi-armed bandits with extreme payoffs Y Yang, A Blanchard, T Sapsis, P Perdikaris Proceedings of the Royal Society A 478 (2260), 20210781, 2022 | 17 | 2022 |
| Differential operator multiplication method for fractional differential equations S Tang, Y Ying, Y Lian, S Lin, Y Yang, GJ Wagner, WK Liu Computational Mechanics 58, 879-888, 2016 | 17 | 2016 |
| Exact boundary condition for semi-discretized Schrödinger equation and heat equation in a rectangular domain G Pang, Y Yang, S Tang Journal of Scientific Computing 72, 1-13, 2017 | 15 | 2017 |
| Stability and convergence analysis of artificial boundary conditions for the Schrödinger equation on a rectangular domain G Pang, Y Yang, X Antoine, S Tang Mathematics of Computation 90 (332), 2731-2756, 2021 | 12 | 2021 |
| Eliminating corner effects in square lattice simulation G Pang, S Ji, Y Yang, S Tang Computational Mechanics 62, 111-122, 2018 | 10 | 2018 |
| Accurate artificial boundary conditions for semi-discretized one-dimensional peridynamics S Ji, G Pang, J Zhang, Y Yang, P Perdikaris Proceedings of the Royal Society A 477 (2250), 20210229, 2021 | 9 | 2021 |
| Deep Learning and Uncertainty Quantification: Methodologies and Applications Y Yang University of Pennsylvania, 2022 | | 2022 |
| A Fast Algorithm for Accurate Boundary Conditions for two-dimensional Schrödinger equation and Heat equation in Rectangular Domain Y YANG, G PANG | | |
Paris PerdikarisUniversity of Pennsylvania確認したメール アドレス: seas.upenn.edu
