GitHub / chenggoj / iGAM-MSI
iGAM-MSI is a repository containing code and trained machine learning models for studying Metal-Support Interactions (MSI) using Interpretable Generalized Additive Models (iGAM). This project leverages the power of iGAM to provide accurate and explainable predictions in materials science. The published work DOI associated with the codes is:
JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/chenggoj%2FiGAM-MSI
PURL: pkg:github/chenggoj/iGAM-MSI
Stars: 1
Forks: 0
Open issues: 0
License: mit
Language: Jupyter Notebook
Size: 305 MB
Dependencies parsed at: Pending
Created at: 12 months ago
Updated at: 5 months ago
Pushed at: 5 months ago
Last synced at: 5 months ago
Topics: density-functional-theory, intrepratable, jupyter-notebook, machine-learning, python3, workflow