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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.comp-ph2025
ECLEIRS: Exact conservation law embedded identification of reduced states for parameterized partial differential equations from sparse and noisy data
Aviral Prakash, Ben S. Southworth, Marc L. Klasky
Multi-query applications such as parameter estimation, uncertainty quantification and design optimization for parameterized PDE systems are expensive due to the high computational…
physics.comp-ph2024
Nonintrusive projection-based reduced order modeling using stable learned differential operators
Aviral Prakash, Yongjie Jessica Zhang
Nonintrusive projection-based reduced order models (ROMs) are essential for dynamics prediction in multi-query applications where access to the source of the underlying full order…