Software

PDE-Discovery:

PDE-READ

Stephany, R., Earls, C.J. (2022) “PDE-READ: Human-readable partial differential equation discovery using deep learning,” Neural Networks, Elsevier, Vol. 154, pp. 360-382 arXiv:2111.00998

Bayesian PDE discovery

Bonneville, C., Earls, C.J. (2022) “Bayesian deep learning for partial differential equation parameter discovery with sparse and noisy data,” Journal of Computational Physics, Elsevier, Vol. 16, 100115 arXiv:2108.04085

 

Green’s Function Discovery:

Greenlearning

Boullé, N., Earls, C.J., Townsend, A. (2022) “Data-driven discovery of Green’s functions with human-understandable deep learning,” Scientific Reports, Vol. 12, No. 4824, Springer Nature.

EmpiricalGreensFunctions

Praveen, H., Boullé, N., Earls, C.J. (2022) “Principled interpolation of Green’s functions learned from data,” IN REVIEW arXiv:2211.06299

 

Finite Element Analysis:

CU-BENs: 3D Nonlinear finite element structural modeling software: geometric and material nonlinear, static and transient dynamic, along with acoustic fluid-structure interaction

Download from GitHub repository

Simple CU-BEN installation guide and tutorial

“Theory manual (incomplete)” for CU-BEN: based on Cornell CEE7790 class notes