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Information theory for data-driven model reduction in physics and
  biology

Information theory for data-driven model reduction in physics and biology

11 December 2023
Matthew S. Schmitt
Maciej Koch-Janusz
Michel Fruchart
Daniel S. Seara
Michael Rust
Vincenzo Vitelli
ArXivPDFHTML

Papers citing "Information theory for data-driven model reduction in physics and biology"

3 / 3 papers shown
Title
Interpretable Machine Learning in Physics: A Review
Interpretable Machine Learning in Physics: A Review
Sebastian Johann Wetzel
Seungwoong Ha
Raban Iten
Miriam Klopotek
Ziming Liu
AI4CE
80
0
0
30 Mar 2025
The mpEDMD Algorithm for Data-Driven Computations of Measure-Preserving
  Dynamical Systems
The mpEDMD Algorithm for Data-Driven Computations of Measure-Preserving Dynamical Systems
Matthew J. Colbrook
33
34
0
06 Sep 2022
Time-lagged autoencoders: Deep learning of slow collective variables for
  molecular kinetics
Time-lagged autoencoders: Deep learning of slow collective variables for molecular kinetics
C. Wehmeyer
Frank Noé
AI4CE
BDL
109
355
0
30 Oct 2017
1