SympNets: Intrinsic structure-preserving symplectic networks for identifying Hamiltonian systems P Jin*, Z Zhang*, A Zhu, Y Tang, GE Karniadakis Neural Networks 132, 166-179, 2020 | 179 | 2020 |
Identifiability and predictability of integer-and fractional-order epidemiological models using physics-informed neural networks E Kharazmi, M Cai, X Zheng, Z Zhang, G Lin, GE Karniadakis Nature Computational Science, 1-10, 2021 | 65 | 2021 |
GFINNs: GENERIC formalism informed neural networks for deterministic and stochastic dynamical systems Z Zhang, Y Shin, GE Karniadakis Philosophical Transactions of the Royal Society A, 2021 | 49 | 2021 |
Learning Poisson systems and trajectories of autonomous systems via Poisson neural networks P Jin, Z Zhang, IG Kevrekidis, GE Karniadakis IEEE Transactions on Neural Networks and Learning Systems, 2022 | 41 | 2022 |
Systems biology: Identifiability analysis and parameter identification via systems-biology-informed neural networks M Daneker, Z Zhang, GE Karniadakis, L Lu Computational Modeling of Signaling Networks, 87-105, 2023 | 35 | 2023 |
An integrated framework for building trustworthy data-driven epidemiological models: Application to the COVID-19 outbreak in New York City S Zhang*, J Ponce*, Z Zhang*, G Lin, GE Karniadakis PLOS Computational Biology 17 (9), 2021 | 28 | 2021 |
Discovering a reaction–diffusion model for Alzheimer’s disease by combining PINNs with symbolic regression Z Zhang, Z Zou, E Kuhl, GE Karniadakis Computer Methods in Applied Mechanics and Engineering 419, 116647, 2024 | 16 | 2024 |
SympOCnet: Solving optimal control problems with applications to high-dimensional multi-agent path planning problems T Meng*, Z Zhang*, J Darbon, GE Karniadakis arXiv preprint arXiv:2201.05475, 2022 | 11 | 2022 |