Molecular Representation for Property Prediction: Wanders in the Chemical Space
Date:
Talk at Department of Chemistry, Carnegie Mellon University, Pittsburgh, Pennsylvania
From the early days of QSAR to the current deep learning models such as variational autoencoders and graph neural networks, molecular representation has been a central theme in cheminformatics. In this talk, I reviwed the history of molecular representation and discussed the current state-of-the-art models for property prediction.