Artificial intelligence (AI) is being increasingly integrated into scientific discovery to augment
and accelerate research, hel** scientists to generate hypotheses, design experiments …

Abstract Machine learning models are increasingly used in materials studies because of
their exceptional accuracy. However, the most accurate machine learning models are …

Applications of deep learning in financial market prediction have attracted widespread
attention from investors and scholars. From convolutional neural networks to recurrent …

Large Language Models (LLMs) have emerged as a transformative power in enhancing
natural language comprehension, representing a significant stride toward artificial general …

Geometric deep learning (GDL) is based on neural network architectures that incorporate
and process symmetry information. GDL bears promise for molecular modelling applications …

Transformer models coupled with a simplified molecular line entry system (SMILES) have
recently proven to be a powerful combination for solving challenges in cheminformatics …

The sustainable production of chemicals from renewable, nonedible biomass has emerged
as an essential alternative to address pressing environmental issues arising from our heavy …

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 …

Automating retrosynthesis with artificial intelligence expedites organic chemistry research in
digital laboratories. However, most existing deep-learning approaches are hard to explain …

Humans use different domain languages to represent, explore, and communicate scientific
concepts. During the last few hundred years, chemists compiled the language of chemical …