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physics.comp-ph2026
Nonlinear GENERIC-Embedded Neural Networks (N-GENNs): Learning GENERIC dynamics with non-quadratic dissipation potentials
VojtÄch Votruba, Vojtěch Votruba, Zequn He +3
We introduce Nonlinear GENERIC-Embedded Neural Networks (N-GENNs), a deep learning framework for discovering evolution equations of systems governed by the nonlinear GENERIC formal…
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…