1 citations · 2 across the 4 of their papers we have counts for
4 papers
Deep Policy Iteration for High-Dimensional Mean-Field Games with Regenerative Reformulation
Shuixin Fang, Shupeng Wang, Zhen Wu +2
This paper develops a deep policy iteration method for high-dimensional finite-horizon mean-field games (MFG). We reformulate the game as a regenerative problem with deterministic…
Pharmacometrics Modeling via Physics-Informed Neural Networks: Integrating Time-Variant Absorption Rates and Fractional Calculus for Enhancing Prediction Accuracy
Nazanin Ahmadi, Shupeng Wang, George Karniadakis
We present a novel method to improve pharmacokinetics modeling, an essential step of drug development. Conventional models frequently fail to fully represent the intricacies of dru…
CMINNs: Compartment Model Informed Neural Networks -- Unlocking Drug Dynamics
Nazanin Ahmadi Daryakenari, Shupeng Wang, George Karniadakis
In the field of pharmacokinetics and pharmacodynamics (PKPD) modeling, which plays a pivotal role in the drug development process, traditional models frequently encounter difficult…
GMC-PINNs: A new general Monte Carlo PINNs method for solving fractional partial differential equations on irregular domains
Shupeng Wang, George Em Karniadakis
Physics-Informed Neural Networks (PINNs) have been widely used for solving partial differential equations (PDEs) of different types, including fractional PDEs (fPDES) [29]. Herein,…