A Hagg, KN Kirschner - Journal of Chemical Information and …, 2023 - ACS Publications
The field of computational chemistry has seen a significant increase in the integration of machine learning concepts and algorithms. In this Perspective, we surveyed 179 open …
Computational Chemistry is currently a synergistic assembly between ab initio calculations, simulation, machine learning (ML) and optimization strategies for describing, solving and …
The field of predictive chemistry relates to the development of models able to describe how molecules interact and react. It encompasses the long-standing task of computer-aided …
AC Mater, ML Coote - Journal of chemical information and …, 2019 - ACS Publications
Machine learning enables computers to address problems by learning from data. Deep learning is a type of machine learning that uses a hierarchical recombination of features to …
Standfirst Over the last decade, we have witnessed the emergence of ever more machine learning applications in all aspects of the chemical sciences. Here, we highlight specific …
The rise and fall of artificial neural networks is well documented in the scientific literature of both computer science and computational chemistry. Yet almost two decades later, we are …
In this review, we highlight recent developments in the application of machine learning for molecular modeling and simulation. After giving a brief overview of the foundations …
J Xia, Y Zhu, Y Du, SZ Li - arXiv preprint arXiv:2210.16484, 2022 - arxiv.org
Deep learning has achieved remarkable success in learning representations for molecules, which is crucial for various biochemical applications, ranging from property prediction to …
Machine learning (ML) has emerged as a general, problem-solving paradigm with many applications in computer vision, natural language processing, digital safety, or medicine. By …