Abstract: A collection of new approaches to building and training neural networks, collectively referred to as deep learning, are attracting attention in theoretical chemistry. Several groups aim to replace computationally expensive ab initio quantum mechanics … Continue Reading ›› Learning a Local-Variable Model of Aromatic and Conjugated Systems
Article available at: https://pubs.acs.org/doi/full/10.1021/acscentsci.7b00405.
Matthew K. Matlock, Na Le Dang, and S. Joshua Swamidass
Abstract: A collection of new approaches to building and training neural networks, collectively referred to as deep learning, are attracting attention in theoretical chemistry. Several groups aim to replace computationally expensive ab initio quantum mechanics … Continue Reading ››
Abstract: A collection of new approaches to building and training neural networks, collectively referred to as deep learning, are attracting attention in theoretical chemistry. Several groups aim to replace computationally expensive ab initio quantum mechanics … Continue Reading ›› 