activity
20182020
most citedClique pooling for graph classification

31 citations · 69 across the 8 of their papers we have counts for

collaborators

11 papers

q-bio.QM20206 cited

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…

cs.LG2020

The Role of Isomorphism Classes in Multi-Relational Datasets

Vijja Wichitwechkarn, Ben Day, Cristian Bodnar +2

Multi-interaction systems abound in nature, from colloidal suspensions to gene regulatory circuits. These systems can produce complex dynamics and graph neural networks have been p…

cs.LG20206 cited

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,…

cs.LG2020

Uncertainty in Neural Relational Inference Trajectory Reconstruction

Vasileios Karavias, Ben Day, Pietro Liò

Neural networks used for multi-interaction trajectory reconstruction lack the ability to estimate the uncertainty in their outputs, which would be useful to better analyse and unde…

cs.LG2020

On Second Order Behaviour in Augmented Neural ODEs

Alexander Norcliffe, Cristian Bodnar, Ben Day +2

Neural Ordinary Differential Equations (NODEs) are a new class of models that transform data continuously through infinite-depth architectures. The continuous nature of NODEs has m…

astro-ph.IM20191 cited

FDL: Mission Support Challenge

Luís F. Simões, Ben Day, Vinutha M. Shreenath +4

The Frontier Development Lab (FDL) is a National Aeronautics and Space Administration (NASA) machine learning program with the stated aim of conducting artificial intelligence rese…