no code implementations • 7 Nov 2021 • Pavol Drotár, Arian Rokkum Jamasb, Ben Day, Cătălina Cangea, Pietro Liò
Molecules are built atom-by-atom inside pockets, guided by structural information from crystallographic data.
no code implementations • NeurIPS Workshop DLDE 2021 • Alexander Luke Ian Norcliffe, Cristian Bodnar, Ben Day, Nikola Simidjievski, Pietro Lio
In Norcliffe et al.[13], we discussed and systematically analysed how Neural ODEs (NODEs) can learn higher-order order dynamics.
1 code implementation • NeurIPS Workshop DLDE 2021 • Alexander Luke Ian Norcliffe, Cristian Bodnar, Ben Day, Jacob Moss, Pietro Lio
To this end, we introduce Neural ODE Processes (NDPs), a new class of stochastic processes determined by a distribution over Neural ODEs.
1 code implementation • 9 Jun 2021 • Ben Day, Ramon Viñas, Nikola Simidjievski, Pietro Liò
Polythetic classifications, based on shared patterns of features that need neither be universal nor constant among members of a class, are common in the natural world and greatly outnumber monothetic classifications over a set of features.
1 code implementation • ICLR Workshop Learning_to_Learn 2021 • Ben Day, Alexander Norcliffe, Jacob Moss, Pietro Liò
Neural ODE Processes approach the problem of meta-learning for dynamics using a latent variable model, which permits a flexible aggregation of contextual information.
2 code implementations • ICLR 2021 • Alexander Norcliffe, Cristian Bodnar, Ben Day, Jacob Moss, Pietro Liò
To address these problems, we introduce Neural ODE Processes (NDPs), a new class of stochastic processes determined by a distribution over Neural ODEs.
no code implementations • 9 Dec 2020 • Thomas Gaudelet, Ben Day, Arian R. Jamasb, Jyothish Soman, Cristian Regep, Gertrude Liu, Jeremy B. R. Hayter, Richard Vickers, Charles Roberts, Jian Tang, David Roblin, Tom L. Blundell, Michael M. Bronstein, Jake P. Taylor-King
Graph Machine Learning (GML) is receiving growing interest within the pharmaceutical and biotechnology industries for its ability to model biomolecular structures, the functional relationships between them, and integrate multi-omic datasets - amongst other data types.
no code implementations • 30 Sep 2020 • Vijja Wichitwechkarn, Ben Day, Cristian Bodnar, Matthew Wales, Pietro Liò
The current training and evaluation procedures for these models through the use of synthetic multi-relational datasets however are agnostic to interaction network isomorphism classes, which produce identical dynamics up to initial conditions.
no code implementations • 29 Sep 2020 • Ben Day, Cătălina Cangea, Arian R. Jamasb, Pietro Liò
Neural Processes (NPs) are powerful and flexible models able to incorporate uncertainty when representing stochastic processes, while maintaining a linear time complexity.
1 code implementation • 24 Jun 2020 • 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 understand the systems they model.
1 code implementation • NeurIPS 2020 • Alexander Norcliffe, Cristian Bodnar, Ben Day, Nikola Simidjievski, Pietro Liò
Neural Ordinary Differential Equations (NODEs) are a new class of models that transform data continuously through infinite-depth architectures.
Ranked #21 on Image Classification on MNIST
1 code implementation • 24 Jun 2019 • Cristian Bodnar, Ben Day, Pietro Lió
We propose a novel algorithm called Proximal Distilled Evolutionary Reinforcement Learning (PDERL) that is characterised by a hierarchical integration between evolution and learning.
2 code implementations • 21 May 2019 • Ezra Webb, Ben Day, Helena Andres-Terre, Pietro Lió
Many complex natural and cultural phenomena are well modelled by systems of simple interactions between particles.
no code implementations • 12 May 2019 • Enxhell Luzhnica, Ben Day, Pietro Liò
Graph classification receives a great deal of attention from the non-Euclidean machine learning community.
1 code implementation • 31 Mar 2019 • Enxhell Luzhnica, Ben Day, Pietro Lio'
We propose a novel graph pooling operation using cliques as the unit pool.
no code implementations • 22 Oct 2018 • Conor Sheehan, Ben Day, Pietro Liò
One-hot encoding is a labelling system that embeds classes as standard basis vectors in a label space.