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

11 citations · 11 across the 3 of their papers we have counts for

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math.NA2025

Parallel-in-Time Solution of Allen-Cahn Equations by Integrating Operator Learning into the Parareal Method

Yuwei Geng, Junqi Yin, Eric C. Cyr +2

While recent advances in deep learning have shown promising efficiency gains in solving time-dependent partial differential equations (PDEs), matching the accuracy of conventional…

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…

math.NA2024★ 11 cited

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

Yuwei Geng, Jasdeep Singh, Lili Ju +2

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