De novo molecular design attempts to search over the chemical space for molecules with
the desired property. Recently, deep learning has gained considerable attention as a …

Burgeoning developments in machine learning (ML) and its rapidly growing adaptations in
chemistry are noteworthy. Motivated by the successful deployments of ML in the realm of …

Deep learning (DL)-based de novo molecular design has recently gained considerable
traction. Many DL-based generative models have been successfully developed to design …

Deep learning approaches have become popular in recent years in the field of de novo
molecular design. While a variety of different methods are available, it is still a challenge to …

The efficient exploration of chemical space to design molecules with intended properties
enables the accelerated discovery of drugs, materials, and catalysts, and is one of the most …

Evolutionary design has gained significant attention as a useful tool to accelerate the design
process by automatically modifying molecular structures to obtain molecules with the target …

In this paper, a prototypical deep evolutionary learning (DEL) process is proposed to
integrate deep generative model and multi-objective evolutionary computation for molecular …

The discovery of molecular structures with desired properties for applications in drug
discovery, crop protection, or chemical biology is among the most impactful scientific …

Materials chemistry is being profoundly influenced by the uptake of machine learning
methodologies. Machine learning techniques, in combination with established techniques …

Conspectus In the domain of reaction development, one aims to obtain higher efficacies as
measured in terms of yield and/or selectivities. During the empirical cycles, an admixture of …