Generative models for molecular discovery: Recent advances and challenges
Abstract Development of new products often relies on the discovery of novel molecules.
While conventional molecular design involves using human expertise to propose …
While conventional molecular design involves using human expertise to propose …
A review of molecular representation in the age of machine learning
DS Wigh, JM Goodman… - Wiley Interdisciplinary …, 2022 - Wiley Online Library
Research in chemistry increasingly requires interdisciplinary work prompted by, among
other things, advances in computing, machine learning, and artificial intelligence. Everyone …
other things, advances in computing, machine learning, and artificial intelligence. Everyone …
Rechargeable batteries of the future—the state of the art from a BATTERY 2030+ perspective
M Fichtner, K Edström, E Ayerbe… - Advanced Energy …, 2022 - Wiley Online Library
The development of new batteries has historically been achieved through discovery and
development cycles based on the intuition of the researcher, followed by experimental trial …
development cycles based on the intuition of the researcher, followed by experimental trial …
Human-and machine-centred designs of molecules and materials for sustainability and decarbonization
Breakthroughs in molecular and materials discovery require meaningful outliers to be
identified in existing trends. As knowledge accumulates, the inherent bias of human intuition …
identified in existing trends. As knowledge accumulates, the inherent bias of human intuition …
Sample efficiency matters: a benchmark for practical molecular optimization
Molecular optimization is a fundamental goal in the chemical sciences and is of central
interest to drug and material design. In recent years, significant progress has been made in …
interest to drug and material design. In recent years, significant progress has been made in …
[HTML][HTML] Recent advances in computational modeling of MOFs: From molecular simulations to machine learning
The reticular chemistry of metal–organic frameworks (MOFs) allows for the generation of an
almost boundless number of materials some of which can be a substitute for the traditionally …
almost boundless number of materials some of which can be a substitute for the traditionally …
SELFIES and the future of molecular string representations
Artificial intelligence (AI) and machine learning (ML) are expanding in popularity for broad
applications to challenging tasks in chemistry and materials science. Examples include the …
applications to challenging tasks in chemistry and materials science. Examples include the …
Structure-based de novo drug design using 3D deep generative models
Deep generative models are attracting much attention in the field of de novo molecule
design. Compared to traditional methods, deep generative models can be trained in a fully …
design. Compared to traditional methods, deep generative models can be trained in a fully …
Machine learning directed drug formulation development
Abstract Machine learning (ML) has enabled ground-breaking advances in the healthcare
and pharmaceutical sectors, from improvements in cancer diagnosis, to the identification of …
and pharmaceutical sectors, from improvements in cancer diagnosis, to the identification of …
GenAICHI: generative AI and HCI
This workshop applies human centered themes to a new and powerful technology,
generative artificial intelligence (AI). Unlike AI systems that produce decisions or …
generative artificial intelligence (AI). Unlike AI systems that produce decisions or …