Outputs (2)

Automatically discovering ordinary differential equations from data with sparse regression (2024)
Journal Article
Egan, K., Li, W., & Carvalho, R. (2024). Automatically discovering ordinary differential equations from data with sparse regression. Communications Physics, 7(1), Article 20. https://doi.org/10.1038/s42005-023-01516-2

Discovering nonlinear differential equations that describe system dynamics from empirical data is a fundamental challenge in contemporary science. While current methods can identify such equations, they often require extensive manual hyperparameter t... Read More about Automatically discovering ordinary differential equations from data with sparse regression.

Automatically identifying ordinary differential equations from data (2023)
Report
Egan, K., Li, W., & Carvalho, R. (2023). Automatically identifying ordinary differential equations from data. Durham University

Discovering nonlinear differential equations that describe system dynamics from empirical data is a fundamental challenge in contemporary science. Here, we propose a methodology to identify dynamical laws by integrating denoising techniques to smooth... Read More about Automatically identifying ordinary differential equations from data.