Unsupervised Manifold Embedding To Encode Molecular Quantum Information For Supervised Learning Of Chemical Data

The article discusses the importance of molecular representation in chemical machine learning and introduces a new method, Manifold Embedding of Molecular Surface (MEMS), to capture surface electronic quantities for predicting molecular interactions. MEMS has shown promising results in solubility prediction using both shallow and deep learning techniques.