SympNets: Intrinsic structure-preserving symplectic networks for identifying Hamiltonian systems. - Pengzhan Jin; Zhen Zhang 029; Aiqing Zhu; Yifa Tang; George Em Karniadakis (Neural Networks, 2020)

GFINNs: GENERIC Formalism Informed Neural Networks for Deterministic and Stochastic Dynamical Systems. - Zhen Zhang 029; Yeonjong Shin; George Em Karniadakis (CoRR, 2021)

Identifiability and predictability of integer- and fractional-order epidemiological models using physics-informed neural networks. - Ehsan Kharazmi; Min Cai; Xiaoning Zheng; Zhen Zhang 029; Guang Lin 001; George Em Karniadakis (Nat. Comput. Sci., 2021)

An integrated framework for building trustworthy data-driven epidemiological models: Application to the COVID-19 outbreak in New York City. - Sheng Zhang; Joan Ponce; Zhen Zhang 029; Guang Lin 001; George E. Karniadakis (PLoS Comput. Biol., 2021)

SympOCnet: Solving optimal control problems with applications to high-dimensional multi-agent path planning problems. - Tingwei Meng; Zhen Zhang 029; Jérôme Darbon; George Em Karniadakis (CoRR, 2022)

Systems Biology: Identifiability analysis and parameter identification via systems-biology informed neural networks. - Mitchell Daneker; Zhen Zhang 029; George Em Karniadakis; Lu Lu 010 (CoRR, 2022)

SympOCnet: Solving Optimal Control Problems with Applications to High-Dimensional Multiagent Path Planning Problems. - Tingwei Meng; Zhen Zhang 029; Jérôme Darbon; George E. Karniadakis (SIAM J. Sci. Comput., 2022)

Discovering a reaction-diffusion model for Alzheimer's disease by combining PINNs with symbolic regression. - Zhen Zhang 029; Zongren Zou; Ellen Kuhl; George Em Karniadakis (CoRR, 2023)

Learning Poisson Systems and Trajectories of Autonomous Systems via Poisson Neural Networks. - Pengzhan Jin; Zhen Zhang 029; Ioannis G. Kevrekidis; George Em Karniadakis (IEEE Trans. Neural Networks Learn. Syst., 2023)

SympGNNs: Symplectic Graph Neural Networks for identifiying high-dimensional Hamiltonian systems and node classification. - Alan John Varghese; Zhen Zhang 029; George Em Karniadakis (CoRR, 2024)

Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling. - Vivek Oommen; Aniruddha Bora; Zhen Zhang 029; George Em Karniadakis (CoRR, 2024)

Coagulo-Net: Enhancing the mathematical modeling of blood coagulation using physics-informed neural networks. - Ying Qian; Ge Zhu; Zhen Zhang 029; Susree Modepalli; Yihao Zheng; Xiaoning Zheng; Galit Frydman; He Li (Neural Networks, 2024)

SympGNNs: Symplectic Graph Neural Networks for identifying high-dimensional Hamiltonian systems and node classification. - Alan John Varghese; Zhen Zhang 029; George Em Karniadakis (Neural Networks, 2025)

A Time-Dependent Symplectic Network for Nonconvex Path Planning Problems with Linear and Nonlinear Dynamics. - Zhen Zhang 029; Chenye Wang; Shanqing Liu; Jérôme Darbon; George Em Karniadakis (SIAM J. Sci. Comput., 2025)

Equilibrium Conserving Neural Operators for Super-Resolution Learning. - Vivek Oommen; Andreas E. Robertson; Daniel Diaz; Coleman Alleman; Zhen Zhang 029; Anthony D. Rollett; George E. Karniadakis; Rémi Dingreville (CoRR, 2025)