3 papers
cs.LG2025
A Variational Framework for Residual-Based Adaptivity in Neural PDE Solvers and Operator Learning
Juan Diego Toscano, Daniel T. Chen, Vivek Oommen +2
Residual-based adaptive strategies are widely used in scientific machine learning but remain largely heuristic. We introduce a unifying variational framework that formalizes these…
physics.flu-dyn2025
Learning Turbulent Flows with Generative Models: Super-resolution, Forecasting, and Sparse Flow Reconstruction
Vivek Oommen, Siavash Khodakarami, Aniruddha Bora +2
Neural operators are promising surrogates for dynamical systems but when trained with standard L2 losses they tend to oversmooth fine-scale turbulent structures. Here, we show that…
cs.LG2025
FMEnets: Flow, Material, and Energy networks for non-ideal plug flow reactor design
Chenxi Wu, Juan Diego Toscano, Khemraj Shukla +7
We propose FMEnets, a physics-informed machine learning framework for the design and analysis of non-ideal plug flow reactors. FMEnets integrates the fundamental governing equation…