1 citations · 1 across the 3 of their papers we have counts for
3 papers
Stochastic force inference via density estimation
Victor Chardès, Suryanarayana Maddu, Michael J. Shelley
Inferring dynamical models from low-resolution temporal data continues to be a significant challenge in biophysics, especially within transcriptomics, where separating molecular pr…
Learning fast, accurate, and stable closures of a kinetic theory of an active fluid
Suryanarayana Maddu, Scott Weady, Michael J. Shelley
Important classes of active matter systems can be modeled using kinetic theories. However, kinetic theories can be high dimensional and challenging to simulate. Reduced-order repre…
Learning locally dominant force balances in active particle systems
Dominik Sturm, Suryanarayana Maddu, Ivo F. Sbalzarini
We use a combination of unsupervised clustering and sparsity-promoting inference algorithms to learn locally dominant force balances that explain macroscopic pattern formation in s…