3 papers
physics.flu-dyn2026
Sparse POD Mode Selection and Manifold Dimensionality Reduction with Neural Networks
Tomoki Koike, Prakash Mohan, Marc T. Henry de Frahan +2
Linear dimensionality reduction methods such as proper orthogonal decomposition (POD) make high-dimensional data amenable to analysis by identifying the principal components, or mo…
math.NA2026
Streaming Operator Inference for Model Reduction of Large-Scale Dynamical Systems
Tomoki Koike, Prakash Mohan, Marc T. Henry de Frahan +2
Projection-based model reduction enables efficient simulation of complex dynamical systems by constructing low-dimensional surrogate models from high-dimensional data. The Operator…
math.DS2025
Operator Inference Aware Quadratic Manifolds with Isotropic Reduced Coordinates for Nonintrusive Model Reduction
Paul Schwerdtner, Prakash Mohan, Julie Bessac +2
Quadratic manifolds for nonintrusive reduced modeling are typically trained to minimize the reconstruction error on snapshot data, which means that the error of models fitted to th…