Code for "A minimalistic approach to physics-informed machine learning using neighbour lists as physics optimized convolutions for inverse problems involving particle systems".

Alessio Alexiadis (Creator)

Chemical Engineering

Dataset

Description

Python files and jupyter notebooks used for the calculation in the manuscript

Date made available	3 Dec 2021
Publisher	University of Birmingham

DOI
10.25500/edata.bham.00000744

1 Article

A minimalistic approach to physics-informed machine learning using neighbour lists as physics-optimized convolutions for inverse problems involving particle systems
Alexiadis, A., 15 Jan 2023, In: Journal of Computational Physics. 473, 111750.
Research output: Contribution to journal › Article › peer-review

Open Access
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