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20242026
most citedGradient Preserving Operator Inference: Data-Driven Reduced-Order Models for Equations with Gradient Structure

11 citations · 14 across the 5 of their papers we have counts for

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3 papers · 1 filter

math.NA2025

Parametric Operator Inference to Simulate the Purging Process in Semiconductor Manufacturing

Seunghyon Kang, Hyeonghun Kim, Boris Kramer

This work presents the application of parametric Operator Inference (OpInf) -- a nonintrusive reduced-order modeling (ROM) technique that learns a low-dimensional representation of…

physics.comp-ph2025★ 3 cited

Physically consistent predictive reduced-order modeling by enhancing Operator Inference with state constraints

Hyeonghun Kim, Boris Kramer

Numerical simulations of complex multiphysics systems, such as char combustion considered herein, yield numerous state variables that inherently exhibit physical constraints. This…

math.NA2025

Data-Driven Reduced-Order Models for Port-Hamiltonian Systems with Operator Inference

Yuwei Geng, Lili Ju, Boris Kramer +1

Hamiltonian operator inference has been developed in [Sharma, H., Wang, Z., Kramer, B., Physica D: Nonlinear Phenomena, 431, p.133122, 2022] to learn structure-preserving reduced-o…