Machine learning interatomic potentials (MLIP) are a topic of very active research, promising to bring the high accuracy of electronic structure methods to large space and long time scales previously ...

In data-driven materials design where the target materials have limited data, the transfer machine learning from large known source materials, becomes a demanding strategy especially across different ...

In the rapidly advancing field of computational biology, a review explores the transformative role of deep learning techniques in revolutionizing protein structure prediction. The review, published in ...

Building fast and highly performant data science applications requires an intimate knowledge of how data can be organized in a computer and how to efficiently perform operations such as sorting, ...