2 citations · 7 across the 19 of their papers we have counts for
6 papers · 1 filter
Sampling via Stochastic Interpolants by Langevin-based Velocity and Initialization Estimation in Flow ODEs
Chenguang Duan, Yuling Jiao, Gabriele Steidl +3
We propose a novel method for sampling from unnormalized Boltzmann densities based on a probability flow ordinary differential equation (ODE) derived from linear stochastic interpo…
A weighted scalar auxiliary variable method for solving gradient flows: bridging the nonlinear energy-based and Lagrange multiplier approaches
Qiong-Ao Huang, Wei Jiang, Jerry Zhijian Yang +1
Two primary scalar auxiliary variable (SAV) approaches are widely applied for simulating gradient flow systems, i.e., the nonlinear energy-based approach and the Lagrange multiplie…
Nonlinear Assimilation via Score-based Sequential Langevin Sampling
Zhao Ding, Chenguang Duan, Yuling Jiao +3
This paper introduces score-based sequential Langevin sampling (SSLS), a novel approach to nonlinear data assimilation within a recursive Bayesian filtering framework. The proposed…
DRM Revisited: A Complete Error Analysis
Yuling Jiao, Ruoxuan Li, Peiying Wu +2
In this work, we address a foundational question in the theoretical analysis of the Deep Ritz Method (DRM) under the over-parameteriztion regime: Given a target precision level, ho…
Solving the inverse source problem of the fractional Poisson equation by MC-fPINNs
Rui Sheng, Peiying Wu, Jerry Zhijian Yang +1
In this paper, we effectively solve the inverse source problem of the fractional Poisson equation using MC-fPINNs. We construct two neural networks and …
A Stabilized Physics Informed Neural Networks Method for Wave Equations
Yuling Jiao, Yuhui Liu, Jerry Zhijian Yang +1
In this article, we propose a novel Stabilized Physics Informed Neural Networks method (SPINNs) for solving wave equations. In general, this method not only demonstrates theoretica…