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20232026
most citedStatistical-Physics-Informed Neural Networks (Stat-PINNs): A Machine Learning Strategy for Coarse-graining Dissipative Dynamics

3 citations · 3 across the 5 of their papers we have counts for

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cs.LG2025

SPIEDiff: robust learning of long-time macroscopic dynamics from short-time particle simulations with quantified epistemic uncertainty

Zequn He, Celia Reina

The data-driven discovery of long-time macroscopic dynamics and thermodynamics of dissipative systems with particle fidelity is hampered by significant obstacles. These include the…

physics.comp-ph2025

EVODMs: variational learning of PDEs for stochastic systems via diffusion models with quantified epistemic uncertainty

Zequn He, Celia Reina

We present Epistemic Variational Onsager Diffusion Models (EVODMs), a machine learning framework that integrates Onsager's variational principle with diffusion models to enable the…