Zobrazeno 1 - 10
of 40
pro vyhledávání: '"Ryan‐Rhys Griffiths"'
Publikováno v:
Frontiers in Artificial Intelligence, Vol 7 (2024)
We deploy a prompt-augmented GPT-4 model to distill comprehensive datasets on the global application of debt-for-nature swaps (DNS), a pivotal financial tool for environmental conservation. Our analysis includes 195 nations and identifies 21 countrie
Externí odkaz:
https://doaj.org/article/483a7dff780c4fddaaf0ab806b5985fb
Publikováno v:
Applied AI Letters, Vol 3, Iss 2, Pp n/a-n/a (2022)
Abstract The task of predicting human motion is complicated by the natural heterogeneity and compositionality of actions, necessitating robustness to distributional shifts as far as out‐of‐distribution (OoD). Here, we formulate a new OoD benchmar
Externí odkaz:
https://doaj.org/article/b318a79b6936468fa49566a967dc17a1
Autor:
Alexander I. Cowen-Rivers, Wenlong Lyu, Rasul Tutunov, Zhi Wang, Antoine Grosnit, Ryan Rhys Griffiths, Alexandre Max Maraval, Hao Jianye, Jun Wang, Jan Peters, Haitham Bou-Ammar
Publikováno v:
Journal of Artificial Intelligence Research. 74:1269-1349
In this work we rigorously analyse assumptions inherent to black-box optimisation hyper-parameter tuning tasks. Our results on the Bayesmark benchmark indicate that heteroscedasticity and non-stationarity pose significant challenges for black-box opt
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a97fe53f0c70f1b70dc6e8de08640b0e
https://doi.org/10.1613/jair.1.13643
https://doi.org/10.1613/jair.1.13643
Reaction additives play a significant role in controlling the reactivity and outcomes of chemical reactions. For example, a recent high-throughput additive screening identified a phthalimide ligand additive for Ni-catalysed photoredox decarboxylative
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4b466a9a743d262d1b8d0bc126e62c43
https://doi.org/10.26434/chemrxiv-2022-nll2j-v2
https://doi.org/10.26434/chemrxiv-2022-nll2j-v2
Autor:
Ryan-Rhys Griffiths, Jake L. Greenfield, Aditya R. Thawani, Arian R. Jamasb, Henry B. Moss, Anthony Bourached, Penelope Jones, William McCorkindale, Alexander A. Aldrick, Matthew J. Fuchter, Alpha A. Lee
Publikováno v:
Chemical science. 13(45)
Photoswitchable molecules display two or more isomeric forms that may be accessed using light. Separating the electronic absorption bands of these isomers is key to selectively addressing a specific isomer and achieving high photostationary states wh
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1a7a8d1acb75725a67810c8f96b93613
https://pubmed.ncbi.nlm.nih.gov/36507171
https://pubmed.ncbi.nlm.nih.gov/36507171
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 art paintings and drawings. Our overall system processes both the ima
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::11d2bd0de19266cdd69300d7ad705f04
Autor:
S. Komossa, Luigi C. Gallo, Dan R. Wilkins, Alpha A. Lee, George Cann, W. N. Alston, Erin Kara, D. J. K. Buisson, Anthony Bourached, Ryan-Rhys Griffiths, Dirk Grupe, Adam Ingram, Michael Parker, Andrew J. Young, Jiachen Jiang
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. Such a reprocessing model would be characterised by lags between X-ray
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9443273e8885581418010b2f89b725e9
Publikováno v:
Applied AI letters. 3(2)
The task of predicting human motion is complicated by the natural heterogeneity and compositionality of actions, necessitating robustness to distributional shifts as far as out-of-distribution (OoD). Here, we formulate a new OoD benchmark based on th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::470d1003f5f6e168f281387459480b3a
https://pubmed.ncbi.nlm.nih.gov/35669063
https://pubmed.ncbi.nlm.nih.gov/35669063
Publikováno v:
Web of Science
Supply chain network data is a valuable asset for businesses wishing to understand their ethical profile, security of supply, and efficiency. Possession of a dataset alone however is not a sufficient enabler of actionable decisions due to incomplete
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::35814c329ae6305bc10097e821ac6128
We describe the application of convolutional neural network style transfer to the problem of improved visualization of underdrawings and ghost-paintings in fine art oil paintings. Such underdrawings and hidden paintings are typically revealed by x-ra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4223afda86a753b3c85835fdd1ec714d