Ryan-Rhys Griffiths

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 28

Top Topics

Gaussian Process

Motion Prediction

Ordinal Regression

Generative Model

Top Venues

Computer Vision and Image Analysis of Art

Mach. Learn. Sci. Technol.

Publications

Nataliya Tkachenko, Simon Frieder, Ryan-Rhys Griffiths, Christoph Nedopil
Analyzing global utilization and missed opportunities in debt-for-nature swaps with generative AI. Frontiers Artif. Intell. 7 (2024)
Ryan-Rhys Griffiths, Leo Klarner, Henry B. Moss, Aditya Ravuri, Sang Truong, Yuanqi Du, Samuel Stanton, Gary Tom, Bojana Rankovic, Arian Rokkum Jamasb, Aryan Deshwal, Julius Schwartz, Austin Tripp, Gregory Kell, Simon Frieder, Anthony Bourached, Alex Chan, Jacob Moss, Chengzhi Guo, Johannes Peter Dürholt, Saudamini Chaurasia, Ji Won Park, Felix Strieth-Kalthoff, Alpha A. Lee, Bingqing Cheng, Alán Aspuru-Guzik, Philippe Schwaller, Jian Tang
GAUCHE: A Library for Gaussian Processes in Chemistry. NeurIPS (2023)
Simon Frieder, Luca Pinchetti, Ryan-Rhys Griffiths, Tommaso Salvatori, Thomas Lukasiewicz, Philipp Christian Petersen, Alexis Chevalier, Julius Berner
Mathematical Capabilities of ChatGPT. CoRR (2023)
Simon Frieder, Luca Pinchetti, Alexis Chevalier, Ryan-Rhys Griffiths, Tommaso Salvatori, Thomas Lukasiewicz, Philipp Petersen, Julius Berner
Mathematical Capabilities of ChatGPT. NeurIPS (2023)
Ryan-Rhys Griffiths
Applications of Gaussian Processes at Extreme Lengthscales: From Molecules to Black Holes. CoRR (2023)
Ryan-Rhys Griffiths, Leo Klarner, Henry B. Moss, Aditya Ravuri, Sang Truong, Bojana Rankovic, Yuanqi Du, Arian Jamasb, Julius Schwartz, Austin Tripp, Gregory Kell, Anthony Bourached, Alex Chan, Jacob Moss, Chengzhi Guo, Alpha A. Lee, Philippe Schwaller, Jian Tang
GAUCHE: A Library for Gaussian Processes in Chemistry. CoRR (2022)
Gregory Kell, Ryan-Rhys Griffiths, Anthony Bourached, David G. Stork
Extracting associations and meanings of objects depicted in artworks through bi-modal deep networks. Computer Vision and Image Analysis of Art (2022)
Ryan-Rhys Griffiths, Alexander A. Aldrick, Miguel Garcia-Ortegon, Vidhi Lalchand, Alpha A. Lee
Achieving robustness to aleatoric uncertainty with heteroscedastic Bayesian optimisation. Mach. Learn. Sci. Technol. 3 (1) (2022)
Alexander I. Cowen-Rivers, Wenlong Lyu, Rasul Tutunov, Zhi Wang, Antoine Grosnit, Ryan-Rhys Griffiths, Alexandre Max Maraval, Jianye Hao, Jun Wang, Jan Peters, Haitham Bou-Ammar
HEBO: An Empirical Study of Assumptions in Bayesian Optimisation. J. Artif. Intell. Res. 74 (2022)
Gregory Kell, Ryan-Rhys Griffiths, Anthony Bourached, David G. Stork
Extracting associations and meanings of objects depicted in artworks through bi-modal deep networks. CoRR (2022)
Anthony Bourached, Robert Gray, Ryan-Rhys Griffiths, Ashwani Jha, Parashkev Nachev
Hierarchical Graph-Convolutional Variational AutoEncoding for Generative Modelling of Human Motion. CoRR (2021)
David G. Stork, Anthony Bourached, George H. Cann, Ryan-Rhys Griffiths
Computational identification of significant actors in paintings through symbols and attributes. Computer Vision and Image Analysis of Art (2021)
Ajmal Aziz, Edward Elson Kosasih, Ryan-Rhys Griffiths, Alexandra Brintrup
Data Considerations in Graph Representation Learning for Supply Chain Networks. CoRR (2021)
Antoine Grosnit, Alexander Imani Cowen-Rivers, Rasul Tutunov, Ryan-Rhys Griffiths, Jun Wang, Haitham Bou-Ammar
Are We Forgetting about Compositional Optimisers in Bayesian Optimisation? J. Mach. Learn. Res. 22 (2021)
Anthony Bourached, George Cann, Ryan-Rhys Griffiths, David G. Stork
Recovery of underdrawings and ghost-paintings via style transfer by deep convolutional neural networks: A digital tool for art scholars. CoRR (2021)
Ryan-Rhys Griffiths, Philippe Schwaller, Alpha A. Lee
Dataset Bias in the Natural Sciences: A Case Study in Chemical Reaction Prediction and Synthesis Design. CoRR (2021)
George H. Cann, Anthony Bourached, Ryan-Rhys Griffiths, David G. Stork
Resolution enhancement in the recovery of underdrawings via style transfer by generative adversarial deep neural networks. Computer Vision and Image Analysis of Art (2021)
Antoine Grosnit, Rasul Tutunov, Alexandre Max Maraval, Ryan-Rhys Griffiths, Alexander Imani Cowen-Rivers, Lin Yang, Lin Zhu, Wenlong Lyu, Zhitang Chen, Jun Wang, Jan Peters, Haitham Bou-Ammar
High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning. CoRR (2021)
George Cann, Anthony Bourached, Ryan-Rhys Griffiths, David G. Stork
Resolution enhancement in the recovery of underdrawings via style transfer by generative adversarial deep neural networks. CoRR (2021)
Anthony Bourached, George H. Cann, Ryan-Rhys Griffiths, David G. Stork
Recovery of underdrawings and ghost-paintings via style transfer by deep convolutional neural networks: A digital tool for art scholars. Computer Vision and Image Analysis of Art (2021)
David G. Stork, Anthony Bourached, George H. Cann, Ryan-Rhys Griffiths
Computational identification of significant actors in paintings through symbols and attributes. CoRR (2021)
Antoine Grosnit, Alexander Imani Cowen-Rivers, Rasul Tutunov, Ryan-Rhys Griffiths, Jun Wang, Haitham Bou-Ammar
Are we Forgetting about Compositional Optimisers in Bayesian Optimisation? CoRR (2020)
Anthony Bourached, Ryan-Rhys Griffiths, Robert Gray, Ashwani Jha, Parashkev Nachev
Generative Model-Enhanced Human Motion Prediction. CoRR (2020)
Aditya R. Thawani, Ryan-Rhys Griffiths, Arian Jamasb, Anthony Bourached, Penelope Jones, William McCorkindale, Alexander A. Aldrick, Alpha A. Lee
The Photoswitch Dataset: A Molecular Machine Learning Benchmark for the Advancement of Synthetic Chemistry. CoRR (2020)
Henry B. Moss, Ryan-Rhys Griffiths
Gaussian Process Molecule Property Prediction with FlowMO. CoRR (2020)
James A. Grant, Alexis Boukouvalas, Ryan-Rhys Griffiths, David S. Leslie, Sattar Vakili, Enrique Munoz de Cote
Adaptive Sensor Placement for Continuous Spaces. ICML (2019)
Ryan-Rhys Griffiths, Miguel Garcia-Ortegon, Alexander A. Aldrick, Alpha A. Lee
Achieving Robustness to Aleatoric Uncertainty with Heteroscedastic Bayesian Optimisation. CoRR (2019)
James A. Grant, Alexis Boukouvalas, Ryan-Rhys Griffiths, David S. Leslie, Sattar Vakili, Enrique Munoz de Cote
Adaptive Sensor Placement for Continuous Spaces. CoRR (2019)