| The photoswitch dataset: a molecular machine learning benchmark for the advancement of synthetic chemistry AR Thawani, RR Griffiths, A Jamasb, A Bourached, P Jones, ... | 25* | 2020 |
| 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 | 19 | 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 | 19 | 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 | 18 | 2022 |
| Generative model‐enhanced human motion prediction A Bourached, RR Griffiths, R Gray, A Jha, P Nachev Applied AI Letters 3 (2), e63, 2022 | 16 | 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 | 14 | 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 | 7 | 2021 |
| Raiders of the lost art A Bourached, G Cann arXiv preprint arXiv:1909.05677, 2019 | 6 | 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 | 5 | 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 | 4 | 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 | 3 | 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 | 2 | 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 | 2 | 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 | 2 | 2022 |
| Unsupervised videographic analysis of rodent behaviour A Bourached, P Nachev arXiv preprint arXiv:1910.11065, 2019 | 2 | 2019 |
| 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 | 1 | 2023 |
| Blocking Versus Non-Blocking Halo Exchange A Bourached University of Edinburgh, 2017 | 1 | 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 | | 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 | | 2023 |
| Deep generative modelling of human behaviour A Bourached PQDT-Global, 2023 | | 2023 |
Ryan-Rhys GriffithsMeta ResearchVerified email at cam.ac.uk
