Machine learning models are poised to make a transformative impact on chemical sciences
by dramatically accelerating computational algorithms and amplifying insights available from …

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 …

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 …

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 …