34 citations · 67 across the 10 of their papers we have counts for
12 papers
GAUCHE: A Library for Gaussian Processes in Chemistry
Ryan-Rhys Griffiths, Leo Klarner, Henry B. Moss +24
We introduce GAUCHE, a library for GAUssian processes in CHEmistry. Gaussian processes have long been a cornerstone of probabilistic machine learning, affording particular advantag…
Extracting associations and meanings of objects depicted in artworks through bi-modal deep networks
Gregory Kell, Ryan-Rhys Griffiths, Anthony Bourached +1
We present a novel bi-modal system based on deep networks to address the problem of learning associations and simple meanings of objects depicted in "authored" images, such as fine…
Hierarchical Graph-Convolutional Variational AutoEncoding for Generative Modelling of Human Motion
Anthony Bourached, Robert Gray, Xiaodong Guan +3
Models of human motion commonly focus either on trajectory prediction or action classification but rarely both. The marked heterogeneity and intricate compositionality of human mot…
Modelling the Multiwavelength Variability of Mrk 335 using Gaussian Processes
Ryan-Rhys Griffiths, Jiachen Jiang, Douglas J. K. Buisson +12
The optical and UV variability of the majority of AGN may be related to the reprocessing of rapidly-changing X-ray emission from a more compact region near the central black hole.…
Computational identification of significant actors in paintings through symbols and attributes
David G. Stork, Anthony Bourached, George H. Cann +1
The automatic analysis of fine art paintings presents a number of novel technical challenges to artificial intelligence, computer vision, machine learning, and knowledge representa…
Resolution enhancement in the recovery of underdrawings via style transfer by generative adversarial deep neural networks
George Cann, Anthony Bourached, Ryan-Rhys Griffiths +1
We apply generative adversarial convolutional neural networks to the problem of style transfer to underdrawings and ghost-images in x-rays of fine art paintings with a special focu…