Anthony Bourached
Cited by
Cited by
The photoswitch dataset: a molecular machine learning benchmark for the advancement of synthetic chemistry
AR Thawani, RR Griffiths, A Jamasb, A Bourached, P Jones, ...
Gauche: A library for Gaussian processes in chemistry
RR Griffiths, L Klarner, H Moss, A Ravuri, S Truong, Y Du, S Stanton, ...
Advances in Neural Information Processing Systems 36, 2024
Modeling the multiwavelength variability of Mrk 335 using Gaussian processes
RR Griffiths, J Jiang, DJK Buisson, D Wilkins, LC Gallo, A Ingram, ...
The Astrophysical Journal 914 (2), 144, 2021
Data-driven discovery of molecular photoswitches with multioutput Gaussian processes
RR Griffiths, JL Greenfield, AR Thawani, AR Jamasb, HB Moss, ...
Chemical Science 13 (45), 13541-13551, 2022
Generative model‐enhanced human motion prediction
A Bourached, RR Griffiths, R Gray, A Jha, P Nachev
Applied AI Letters 3 (2), e63, 2022
Recovery of underdrawings and ghost-paintings via style transfer by deep convolutional neural networks: A digital tool for art scholars
A Bourached, G Cann, RR Griffiths, DG Stork
Electronic Imaging: Computer Vision and Image Analysis of Art 13 (14), pp 42 …, 2021
Computational identification of significant actors in paintings through symbols and attributes
DG Stork, A Bourached, GH Cann, RR Griffiths
Electronic Imaging: Computer Vision and Image Analysis of Art 33, pp 15-1 - 15-8, 2021
Raiders of the lost art
A Bourached, G Cann
arXiv preprint arXiv:1909.05677, 2019
Extracting associations and meanings of objects depicted in artworks through bi-modal deep networks
G Kell, RR Griffiths, A Bourached, DG Stork
arXiv preprint arXiv:2203.07026, 2022
Resolution enhancement in the recovery of underdrawings via style transfer by generative adversarial deep neural networks
GH Cann, A Bourached, RR Griffths, DG Stork
Electronic Imaging 2021 (14), 17-1-17-8(8), 2021
Hierarchical Graph-Convolutional Variational AutoEncoding for Generative Modelling of Human Motion
A Bourached, R Gray, X Guan, RR Griffiths, A Jha, P Nachev
arXiv preprint arXiv:2111.12602, 2021
Scaling behaviours of deep learning and linear algorithms for the prediction of stroke severity
A Bourached, AK Bonkhoff, MD Schirmer, RW Regenhardt, M Bretzner, ...
Brain Communications 6 (1), fcae007, 2024
Recovering lost artworks by deep neural networks: Motivations, methodology, and proof-of-concept simulations
J Eriksson, GH Cann, A Bourached, DG Stork
Electronic Imaging 35, 1-7, 2023
GAUCHE: A library for Gaussian processes and Bayesian optimisation in chemistry
RR Griffiths, L Klarner, A Ravuri, S Truong, B Rankovic, Y Du, A Jamasb, ...
ICML 2022 Workshop on Adaptive Experimental Design and Active Learning in …, 2022
Unsupervised videographic analysis of rodent behaviour
A Bourached, P Nachev
arXiv preprint arXiv:1910.11065, 2019
Blocking Versus Non-Blocking Halo Exchange
A Bourached
University of Edinburgh, 2017
Abstract TMP72: Multimodal Prediction Of Stroke Severity
AK Bonkhoff, A Cohen, W Drew, MA Ferguson, C Lin, F Schaper, ...
Stroke 54 (Suppl_1), ATMP72-ATMP72, 2023
Abstract WMP58: Scaling Behaviors Of Deep Learning And Linear Algorithms For The Prediction Of Stroke Severity
AP Bourached, AK Bonkhoff, MD Schirmer, RW Regenhardt, S Hong, ...
Stroke 54 (Suppl_1), AWMP58-AWMP58, 2023
Style transfer for improved visualization of underdrawings and ghost paintings: An application to a work by Vincent van Gogh
A Bourached, GH Cann, RR Griffiths, J Eriksson, DG Stork
Electronic Imaging 35, 1-5, 2023
Deep generative modelling of human behaviour
A Bourached
PQDT-Global, 2023
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