Molecular representation learning (MRL) has shown promise in accelerating drug development by predicting chemical properties. However, imperfectly annotation among datasets pose challenges in model ...

Pretraining on a large number of unlabeled 3D molecules has showcased superiority in various scientific applications. However, prior efforts typically focus on pretraining models in a specific domain, ...

Researchers at Carnegie Mellon University have developed a molecular machine learning representation that integrates stereoelectronic data from quantum chemistry, enabling faster and more accurate ...