6 papers
Partial Regularity for the Three-dimensional Stochastic Ericksen--Leslie equations
Hengrong Du, Chuntian Wang
In this article, we investigate the global existence of martingale suitable weak solutions to stochastic Ericksen-Leslie equations with additive noise in a 3D torus. The notion of…
Exploring Non-Convex Discrete Energy Landscapes: An Efficient Langevin-Like Sampler with Replica Exchange
Haoyang Zheng, Hengrong Du, Ruqi Zhang +1
Gradient-based Discrete Samplers (GDSs) are effective for sampling discrete energy landscapes. However, they often stagnate in complex, non-convex settings. To improve exploration,…
Non-Reversible Langevin Algorithms for Constrained Sampling
Hengrong Du, Qi Feng, Changwei Tu +2
We consider the constrained sampling problem where the goal is to sample from a target distribution on a constrained domain. We propose skew-reflected non-reversible Langevin dynam…
Optimal Stochastic Trace Estimation in Generative Modeling
Xinyang Liu, Hengrong Du, Wei Deng +1
Hutchinson estimators are widely employed in training divergence-based likelihoods for diffusion models to ensure optimal transport (OT) properties. However, this estimator often s…
Constrained Exploration via Reflected Replica Exchange Stochastic Gradient Langevin Dynamics
Haoyang Zheng, Hengrong Du, Qi Feng +2
Replica exchange stochastic gradient Langevin dynamics (reSGLD) is an effective sampler for non-convex learning in large-scale datasets. However, the simulation may encounter stagn…
A New Hybrid Automaton Framework with Partial Differential Equation Dynamics
Tianshu Bao, Hengrong Du, Weiming Xiang +1
This paper presents the syntax and semantics of a novel type of hybrid automaton (HA) with partial differential equation (PDE) dynamic, partial differential hybrid automata (PDHA).…