collaborators

7 papers

math.NA2026

Weak Adversarial Neural Pushforward Method for Boltzmann Equation

Jenia Fardousi Koly, Andrew Qing He, Wei Cai

In this paper, we extend a weak adversary neural network pushforward method for solving time dependent Boltzmann equation and a weak formulation of the collision operator is propos…

quant-ph2026

Weak Adversarial Neural Pushforward Method for the Wigner Transport Equation

Andrew Qing He, Wei Cai, Sihong Shao

We extend the Weak Adversarial Neural Pushforward Method to the Wigner transport equation governing the phase-space dynamics of quantum systems. The central contribution is a struc…

math.NA2026

Weak Adversarial Neural Pushforward Method for the McKean-Vlasov / Mean-Field Fokker-Planck Equation

Andrew Qing He, Wei Cai

We extend the Weak Adversarial Neural Pushforward Method (WANPM) to the McKean--Vlasov mean-field Fokker--Planck equation, covering both the stationary and time-dependent cases. Th…

math.NA2026

Weak Adversarial Neural Pushforward Method for Fractional Fokker-Planck Equations

Andrew Qing He, Wei Cai

We extend the Weak Adversarial Neural Pushforward Method (WANPM) to fractional Fokker-Planck equations, in which the classical Laplacian diffusion operator is replaced by the fract…

math.NA2026

Neural Pushforward Samplers for the Fokker-Planck Equation on Embedded Riemannian Manifolds

Andrew Qing He, Wei Cai

In this paper, we extend the Weak Adversarial Neural Pushforward Method to the Fokker--Planck equation on compact embedded Riemannian manifolds. The method represents the solution…

math.NA2025

Learning Neural Pushforward Samplers for Distributions from Fokker-Planck Equations by Weak Adversarial Training

Andrew Qing He, Wei Cai

This paper presents a new method for solving Fokker-Planck equations (FPE) by learning a neural sampler for the distribution given by the FPE via an adversarial training based on a…