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Yang-yang Tan

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#machine learning Preprint Sep 2026

Generative Modeling of Stochastic Dynamics for Long-Time Evolution

Exact stochastic equations for non-equilibrium dynamics are rarely accessible. We show that the long-time evolution of stochastic dynamics can be predicted from configuration pairs at a fixed short time lag, without knowledge of the equation of motion. Generative diffusion models learn the finite-time transition kernel...

Yang-Yang Tan, Jin-Yang Li, Ling-Xiao Wang · 0 citations
Preprint Jul 2026

Diffusion Models for Sampling Near Criticality in Lattice Field Theories

We investigate generative diffusion models as denoising samplers for two- and three-dimensional lattice $\phi^4$ theory across the symmetric, near-critical, and broken phases. Validated against ensembles generated by Fourier-accelerated HMC combined with Wolff cluster updates, the reverse-SDE sampler reproduces scalar...

Yang-yang Tan, G. Aarts, Diaa E. Habibi et al. · 3 citations

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