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cs.LG2026
GeoQ: Geometry-Aware Conditional Quantile Error Estimation for Scientific Surrogate Models
Khoa Nguyen, Daniel Serino, Aviral Prakash +1
Neural-network surrogate models are increasingly used to accelerate scientific simulations, but their deployment in extrapolative and autoregressive settings requires input-depende…
physics.comp-ph2026
Structure-preserving variational neural fields: Uncertainty-quantified reduced-order modeling of nonlinear conservation laws
Aviral Prakash, Marc L. Klasky
Reduced-order models, such as latent dynamics models, are becoming mainstream for accelerating simulations for parameterized physical systems governed by nonlinear conservation law…
physics.flu-dyn2026
Discovery of Sparse Invariant Subgrid-Scale Closures via Dissipation-Controlled Training for Large Eddy Simulation on Anisotropic Grids
Samantha Friess, Aviral Prakash, John A. Evans
Neural networks offer highly expressive turbulence closures, yet their complexity obscures the physical mechanisms they aim to model, and their computational cost can limit their t…