8 papers
Training-free score-based diffusion for parameter-dependent stochastic dynamical systems
Minglei Yang, Sicheng He
Simulating parameter-dependent stochastic differential equations (SDEs) presents significant computational challenges, as separate high-fidelity simulations are typically required…
Error estimates of a training-free diffusion model for high-dimensional sampling
Pengjun Wang, Zezhong Zhang, Minglei Yang +3
Score-based diffusion models are a powerful class of generative models, but their practical use often depends on training neural networks to approximate the score function. Trainin…
An efficient probabilistic scheme for the exit time probability of -stable Lévy process
Minglei Yang, Diego del-Castillo-Negrete, Guannan Zhang
The α-stable Lévy process, commonly used to describe Lévy flight, is characterized by discontinuous jumps and is widely used to model anomalous transport phenomena. In this study,…
A Rapid Physics-Informed Machine Learning Framework Based on Extreme Learning Machine for Inverse Stefan Problems
Pei-Zhi Zhuang, Ming-Yue Yang, Fei Ren +2
The inverse Stefan problem, as a typical phase-change problem with moving boundaries, finds extensive applications in science and engineering. Recent years have seen the applicatio…
Gravitational-wave inference at GPU speed: A bilby-like nested sampling kernel within blackjax-ns
Metha Prathaban, David Yallup, James Alvey +3
We present a GPU-accelerated implementation of the gravitational-wave Bayesian inference pipeline for parameter estimation and model comparison. Specifically, we implement the `acc…
Generative AI Models for Learning Flow Maps of Stochastic Dynamical Systems in Bounded Domains
Minglei Yang, Yanfang Liu, Diego del-Castillo-Negrete +2
Simulating stochastic differential equations (SDEs) in bounded domains, presents significant computational challenges due to particle exit phenomena, which requires accurate modeli…
Optimal Overlapping Tomography
Kiara Hansenne, Rui Qu, Lisa T. Weinbrenner +7
Characterising large-scale quantum systems is central to fundamental physics and essential for applications of quantum technologies. While a full characterisation requires exponent…
A family of self-orthogonal divisible codes with locality 2
Ziling Heng, Mengjie Yang, Yang Ming
Linear codes are widely studied due to their applications in communication, cryptography, quantum codes, distributed storage and many other fields. In this paper, we use the trace…