3 citations · 6 across the 7 of their papers we have counts for
4 papers · 1 filter
Two Adjoint Perspectives on Fokker-Planck Optimization: A Microscopic-Macroscopic Correspondence
Kathrin Hellmuth, Qin Li, Yunan Yang
The Fokker-Planck equation admits both a macroscopic Eulerian description through probability densities and a microscopic Lagrangian description through stochastic trajectories. Co…
Data selection: at the interface of PDE-based inverse problem and randomized linear algebra
Kathrin Hellmuth, Ruhui Jin, Qin Li +1
All inverse problems rely on data to recover unknown parameters, yet not all data are equally informative. This raises the central question of data selection. A distinctive challen…
Local sensitivity-preserving random data down-sampling for experimental design
Kathrin Hellmuth, Christian Klingenberg, Qin Li
The quality of numerical reconstructions for unknown parameters in inverse problems depends fundamentally on the selection of experimental data. To ensure a robust reconstruction,…
Reconstructing the kinetic chemotaxis kernel using macroscopic data: well-posedness and ill-posedness
Kathrin Hellmuth, Christian Klingenberg, Qin Li +1
Bacterial motion is steered by external stimuli (chemotaxis), and the motion described on the mesoscopic scale is uniquely determined by a parameter that models velocity change…