ASGN: An active semi-supervised graph neural network for molecular property prediction Z Hao, C Lu, Z Huang, H Wang, Z Hu, Q Liu, E Chen, C Lee Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020 | 134 | 2020 |
Heterogeneous Risk Minimization J Liu, Z Hu, P Cui, B Li, Z Shen International Conference on Machine Learning (ICML), 2021 | 125 | 2021 |
When Do Extended Physics-Informed Neural Networks (XPINNs) Improve Generalization? Z Hu, AD Jagtap, GE Karniadakis, K Kawaguchi SIAM Journal on Scientific Computing, 2021 | 95 | 2021 |
Augmented Physics-Informed Neural Networks (APINNs): A gating network-based soft domain decomposition methodology Z Hu, AD Jagtap, GE Karniadakis, K Kawaguchi Engineering Applications of Artificial Intelligence, 2022 | 49 | 2022 |
Kernelized Heterogeneous Risk Minimization J Liu*, Z Hu*, P Cui, B Li, Z Shen Advances in Neural Information Processing Systems (NeurIPS), 2021 | 33* | 2021 |
Tackling the Curse of Dimensionality with Physics-Informed Neural Networks Z Hu, K Shukla, GE Karniadakis, K Kawaguchi Neural Networks, 2023 | 30 | 2023 |
Hutchinson trace estimation for high-dimensional and high-order physics-informed neural networks Z Hu, Z Shi, GE Karniadakis, K Kawaguchi Computer Methods in Applied Mechanics and Engineering, 2023 | 8 | 2023 |
Bias-variance trade-off in physics-informed neural networks with randomized smoothing for high-dimensional PDEs Z Hu, Z Yang, Y Wang, GE Karniadakis, K Kawaguchi arXiv preprint arXiv:2311.15283, 2023 | 6 | 2023 |
D4FT: A Deep Learning Approach to Kohn-Sham Density Functional Theory T Li, M Lin, Z Hu, K Zheng, G Vignale, K Kawaguchi, AH Castro Neto, ... International Conference on Learning Representations (ICLR, notable-top-25%), 2023 | 6 | 2023 |
Score-based physics-informed neural networks for high-dimensional Fokker-Planck equations Z Hu, Z Zhang, GE Karniadakis, K Kawaguchi arXiv preprint arXiv:2402.07465, 2024 | 3 | 2024 |
Tensor neural networks for high-dimensional Fokker-Planck equations T Wang, Z Hu, K Kawaguchi, Z Zhang, GE Karniadakis arXiv preprint arXiv:2404.05615, 2024 | 1 | 2024 |
Neural Integral Functionals Z Hu, T Li, Z Shi, K Zheng, G Vignale, K Kawaguchi, S Yan, M Lin ICLR 2023 Workshop on Physics for Machine Learning, 2023 | 1 | 2023 |
Score-fPINN: Fractional Score-Based Physics-Informed Neural Networks for High-Dimensional Fokker-Planck-Levy Equations Z Hu, Z Zhang, GE Karniadakis, K Kawaguchi arXiv preprint arXiv:2406.11676, 2024 | | 2024 |
Tackling the Curse of Dimensionality in Fractional and Tempered Fractional PDEs with Physics-Informed Neural Networks Z Hu, K Kawaguchi, Z Zhang, GE Karniadakis arXiv preprint arXiv:2406.11708, 2024 | | 2024 |
Generalization in Neural Operator: Irregular Domains, Orthogonal Basis, and Super-Resolution Z Hu, Z Hao, T Li, Z Shi, K Kawaguchi, M Lin | | 2023 |