DG-GL: Differential geometry-based geometric learning of molecular datasets.
Journal:
International journal for numerical methods in biomedical engineering
Published Date:
Feb 7, 2019
Abstract
MOTIVATION: Despite its great success in various physical modeling, differential geometry (DG) has rarely been devised as a versatile tool for analyzing large, diverse, and complex molecular and biomolecular datasets because of the limited understanding of its potential power in dimensionality reduction and its ability to encode essential chemical and biological information in differentiable manifolds.