Ryan-Rhys Griffiths

According to our database, Ryan-Rhys Griffiths authored at least 23 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

Analyzing global utilization and missed opportunities in debt-for-nature swaps with generative AI.

Nataliya Tkachenko, Simon Frieder, Ryan-Rhys Griffiths, Christoph Nedopil

Frontiers Artif. Intell., 2024

Aviary: training language agents on challenging scientific tasks.

Siddharth Narayanan, James D. Braza, Ryan-Rhys Griffiths, Manvitha Ponnapati, Albert Bou, Jon M. Laurent, Ori Kabeli, Geemi P. Wellawatte, Sam Cox, Samuel G. Rodriques, Andrew D. White

CoRR, 2024

Data for Mathematical Copilots: Better Ways of Presenting Proofs for Machine Learning.

Simon Frieder, Jonas Bayer, Katherine M. Collins, Julius Berner, Jacob Loader, András Juhász, Fabian Ruehle, Sean Welleck, Gabriel Poesia, Ryan-Rhys Griffiths, Adrian Weller, Anirudh Goyal, Thomas Lukasiewicz, Timothy Gowers

CoRR, 2024

RealMedQA: A pilot biomedical question answering dataset containing realistic clinical questions.

Gregory Kell, Angus Roberts, Serge Umansky, Yuti Khare, Najma Ahmed, Nikhil Patel, Chloe Simela, Jack Coumbe, Julian Rozario, Ryan-Rhys Griffiths, Iain James Marshall

CoRR, 2024

2023

Applications of Gaussian Processes at Extreme Lengthscales: From Molecules to Black Holes.

Ryan-Rhys Griffiths

CoRR, 2023

GAUCHE: A Library for Gaussian Processes in Chemistry.

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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Mathematical Capabilities of ChatGPT.

Simon Frieder, Luca Pinchetti, Alexis Chevalier, Ryan-Rhys Griffiths, Tommaso Salvatori, Thomas Lukasiewicz, Philipp Petersen, Julius Berner

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Achieving robustness to aleatoric uncertainty with heteroscedastic Bayesian optimisation.

Ryan-Rhys Griffiths, Alexander A. Aldrick, Miguel Garcia-Ortegon, Vidhi Lalchand, Alpha A. Lee

Mach. Learn. Sci. Technol., 2022

HEBO: An Empirical Study of Assumptions in Bayesian Optimisation.

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

J. Artif. Intell. Res., 2022

GAUCHE: A Library for Gaussian Processes in Chemistry.

Ryan-Rhys Griffiths, Leo Klarner, Henry B. Moss, Aditya Ravuri, Sang Truong, Bojana Rankovic, Yuanqi Du, Arian R. Jamasb, Julius Schwartz, Austin Tripp, Gregory Kell, Anthony Bourached, Alex Chan, Jacob Moss, Chengzhi Guo, Alpha A. Lee, Philippe Schwaller, Jian Tang

CoRR, 2022

Extracting associations and meanings of objects depicted in artworks through bi-modal deep networks.

Gregory Kell, Ryan-Rhys Griffiths, Anthony Bourached, David G. Stork

Proceedings of the Computer Vision and Image Analysis of Art 2022, 2022

2021

Are We Forgetting about Compositional Optimisers in Bayesian Optimisation?

Antoine Grosnit, Alexander I. Cowen-Rivers, Rasul Tutunov, Ryan-Rhys Griffiths, Jun Wang, Haitham Bou-Ammar

J. Mach. Learn. Res., 2021

Hierarchical Graph-Convolutional Variational AutoEncoding for Generative Modelling of Human Motion.

Anthony Bourached, Robert J. Gray, Ryan-Rhys Griffiths, Ashwani Jha, Parashkev Nachev

CoRR, 2021

Data Considerations in Graph Representation Learning for Supply Chain Networks.

Ajmal Aziz, Edward Elson Kosasih, Ryan-Rhys Griffiths, Alexandra Brintrup

CoRR, 2021

High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning.

Antoine Grosnit, Rasul Tutunov, Alexandre Max Maraval, Ryan-Rhys Griffiths, Alexander I. Cowen-Rivers, Lin Yang, Lin Zhu, Wenlong Lyu, Zhitang Chen, Jun Wang, Jan Peters, Haitham Bou-Ammar

CoRR, 2021

Dataset Bias in the Natural Sciences: A Case Study in Chemical Reaction Prediction and Synthesis Design.

Ryan-Rhys Griffiths, Philippe Schwaller, Alpha A. Lee

CoRR, 2021

Computational identification of significant actors in paintings through symbols and attributes.

David G. Stork, Anthony Bourached, George H. Cann, Ryan-Rhys Griffiths

Proceedings of the Computer Vision and Image Analysis of Art 2021, 2021

Resolution enhancement in the recovery of underdrawings via style transfer by generative adversarial deep neural networks.

George H. Cann, Anthony Bourached, Ryan-Rhys Griffiths, David G. Stork

Proceedings of the Computer Vision and Image Analysis of Art 2021, 2021

Recovery of underdrawings and ghost-paintings via style transfer by deep convolutional neural networks: A digital tool for art scholars.

Anthony Bourached, George H. Cann, Ryan-Rhys Griffiths, David G. Stork

Proceedings of the Computer Vision and Image Analysis of Art 2021, 2021

2020

Generative Model-Enhanced Human Motion Prediction.

Anthony Bourached, Ryan-Rhys Griffiths, Robert J. Gray, Ashwani Jha, Parashkev Nachev

CoRR, 2020

Gaussian Process Molecule Property Prediction with FlowMO.

Henry B. Moss, Ryan-Rhys Griffiths

CoRR, 2020

2019

Achieving Robustness to Aleatoric Uncertainty with Heteroscedastic Bayesian Optimisation.

Ryan-Rhys Griffiths, Miguel Garcia-Ortegon, Alexander A. Aldrick, Alpha A. Lee

CoRR, 2019

Adaptive Sensor Placement for Continuous Spaces.

James A. Grant, Alexis Boukouvalas, Ryan-Rhys Griffiths, David S. Leslie, Sattar Vakili, Enrique Munoz de Cote

Proceedings of the 36th International Conference on Machine Learning, 2019