Machine learning methods for molecule predictions use various representations of molecules such as in the form of strings or graphs. As an extension of graph representation learning, Probst and colleagues propose to represent a molecule as a set of atoms, to better capture the underlying chemical nature, and demonstrate improved performance in a range of machine learning tasks.
- Maria Boulougouri
- Pierre Vandergheynst
- Daniel Probst
