Molecular machine learning (ML) underpins critical workflows in drug discovery, material science, and catalyst optimization by rapidly predicting molecular interactions and properties. For instance, ...

GNN, a graph neural network that combines cross-attention-based multi-omics integration with long-tail expert routing to ...

Researchers at The University of Manchester have created a physics‑informed machine‑learning model that can run molecular simulations for unprecedented lengths of time, even at temperatures as high as ...

In recent years, the artificial intelligence (AI) conversation has been dominated by increasingly capable large language models. Every few months, models improve on mathematical reasoning and coding ...

Researchers at KTH Royal Institute of Technology used multi-omics analysis and machine learning to uncover molecular features ...

Tsinghua University researchers introduce FuelProp-LM, a novel framework combining instruction tuning and dynamic in-context learning to predict multiple fuel properties directly from molecular SMILES ...