6 citations · 13 across the 3 of their papers we have counts for
4 papers
Structure-aware generation of drug-like molecules
Pavol Drotár, Arian Rokkum Jamasb, Ben Day +2
Structure-based drug design involves finding ligand molecules that exhibit structural and chemical complementarity to protein pockets. Deep generative methods have shown promise in…
On Graph Neural Network Ensembles for Large-Scale Molecular Property Prediction
Edward Elson Kosasih, Joaquin Cabezas, Xavier Sumba +5
In order to advance large-scale graph machine learning, the Open Graph Benchmark Large Scale Challenge (OGB-LSC) was proposed at the KDD Cup 2021. The PCQM4M-LSC dataset defines a…
Utilising Graph Machine Learning within Drug Discovery and Development
Thomas Gaudelet, Ben Day, Arian R. Jamasb +11
Graph Machine Learning (GML) is receiving growing interest within the pharmaceutical and biotechnology industries for its ability to model biomolecular structures, the functional r…
Message Passing Neural Processes
Ben Day, Cătălina Cangea, Arian R. Jamasb +1
Neural Processes (NPs) are powerful and flexible models able to incorporate uncertainty when representing stochastic processes, while maintaining a linear time complexity. However,…