4 papers
Topological Feature Compression for Molecular Graph Neural Networks
Rahul Khorana
Recent advances in molecular representation learning have produced highly effective encodings of molecules for numerous cheminformatics and bioinformatics tasks. However, extractin…
Families of Optimal Transport Kernels for Cell Complexes
Rahul Khorana
Recent advances have discussed cell complexes as ideal learning representations. However, there is a lack of available machine learning methods suitable for learning on CW complexe…
Polyatomic Complexes: A topologically-informed learning representation for atomistic systems
Rahul Khorana, Marcus Noack, Jin Qian
A representation of a molecule or material should be invariant to the symmetries of physics, unique, continuous, efficient and general. These properties, however, are hard to satis…
CW-CNN & CW-AN: Convolutional Networks and Attention Networks for CW-Complexes
Rahul Khorana
We present a novel framework for learning on CW-complex structured data points. Recent advances have discussed CW-complexes as ideal learning representations for problems in chemin…