Deep learning has become a powerful and frequently employed tool for the prediction of
molecular properties, thus creating a need for open-source and versatile software solutions …

Organic molecules and polymers have a broad range of applications in biomedical,
chemical, and materials science fields. Traditional design approaches for organic molecules …

A pervasive challenge in drug design is determining how to expand a ligand─ a small
molecule that binds to a target biomolecule─ in order to improve various properties of the …

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

In this paper, the significant development, current challenges and future opportunities in the
field of chemical product design using computer-aided molecular design (CAMD) tools are …

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 …

The design of molecules and materials with tailored properties is challenging, as candidate
molecules must satisfy multiple competing requirements that are often difficult to measure or …

In the space of only a few years, deep generative modeling has revolutionized how we think
of artificial creativity, yielding autonomous systems which produce original images, music …

Conspectus The ongoing revolution of the natural sciences by the advent of machine
learning and artificial intelligence sparked significant interest in the material science …

Conspectus Recent advances in computer hardware and software have led to a revolution
in deep neural networks that has impacted fields ranging from language translation to …