| When and why PINNs fail to train: A neural tangent kernel perspective S Wang, X Yu, P Perdikaris Journal of Computational Physics 449, 110768, 2022 | 825 | 2022 |
| DeepOHeat: operator learning-based ultra-fast thermal simulation in 3D-IC design Z Liu, Y Li, J Hu, X Yu, S Shiau, X Ai, Z Zeng, Z Zhang 2023 60th ACM/IEEE Design Automation Conference (DAC), 1-6, 2023 | 11 | 2023 |
| Tensor-Compressed Back-Propagation-Free Training for (Physics-Informed) Neural Networks Y Zhao*, X Yu*, Z Chen, Z Liu, S Liu, Z Zhang arXiv preprint arXiv:2308.09858, 2023 | 9 | 2023 |
| Pifon-ept: Mr-based electrical property tomography using physics-informed fourier networks X Yu, JEC Serrallés, II Giannakopoulos, Z Liu, L Daniel, R Lattanzi, ... IEEE Journal on Multiscale and Multiphysics Computational Techniques, 2023 | 6 | 2023 |
| TT-PINN: A Tensor-Compressed Neural PDE Solver for Edge Computing Z Liu*, X Yu*, Z Zhang Hardware-Aware Efficient Training at ICML 2022, 2022 | 6 | 2022 |
| MR-Based Electrical Property Reconstruction Using Physics-Informed Neural Networks X Yu, JEC Serrallés, II Giannakopoulos, Z Liu, L Daniel, R Lattanzi, ... QMR Lucca workshop on MR Phase, Magnetic Susceptibility and Electrical …, 2022 | 2 | 2022 |
| Real-Time FJ/MAC PDE Solvers via Tensorized, Back-Propagation-Free Optical PINN Training Y Zhao, X Xiao, X Yu, Z Liu, Z Chen, G Kurczveil, RG Beausoleil, Z Zhang Machine Learning with New Compute Paradigms at NeurIPS 2023, 2023 | 1 | 2023 |
| Photonic KAN: a Kolmogorov-Arnold network inspired efficient photonic neuromorphic architecture Y Peng, S Hooten, X Yu, T Van Vaerenbergh, Y Yuan, X Xiao, B Tossoun, ... arXiv preprint arXiv:2408.08407, 2024 | | 2024 |
| Separable Operator Networks X Yu, S Hooten, Z Liu, Y Zhao, M Fiorentino, T Van Vaerenbergh, Z Zhang arXiv preprint arXiv:2407.11253, 2024 | | 2024 |
Paris PerdikarisUniversity of Pennsylvania || Microsoft ResearchVerified email at seas.upenn.edu
