Ryan-Rhys Griffiths

32 papers A* 3Journal 25Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Neural Nonmyopic Bayesian Optimization in Dynamic Cost Settings. CoRR Sang T. Truong, Duc Q. Nguyen, Willie Neiswanger, Ryan-Rhys Griffiths, Stefano Ermon, Nick Haber, Sanmi Koyejo
2025	J	`jnl`	Training a Scientific Reasoning Model for Chemistry. CoRR Siddharth Narayanan, James D. Braza, Ryan-Rhys Griffiths, Albert Bou, Geemi P. Wellawatte, Mayk Caldas Ramos, Ludovico Mitchener, Samuel G. Rodriques, Andrew D. White
2024	J	`jnl`	Analyzing global utilization and missed opportunities in debt-for-nature swaps with generative AI. Frontiers Artif. Intell. Nataliya Tkachenko, Simon Frieder, Ryan-Rhys Griffiths, Christoph Nedopil
2024	J	`jnl`	Aviary: training language agents on challenging scientific tasks. CoRR 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
2024	J	`jnl`	Data for Mathematical Copilots: Better Ways of Presenting Proofs for Machine Learning. CoRR 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
2024	J	`jnl`	RealMedQA: A pilot biomedical question answering dataset containing realistic clinical questions. CoRR Gregory Kell, Angus Roberts, Serge Umansky, Yuti Khare, Najma Ahmed, Nikhil Patel, Chloe Simela, Jack Coumbe, Julian Rozario, Ryan-Rhys Griffiths, Iain James Marshall
2023	J	`jnl`	Applications of Gaussian Processes at Extreme Lengthscales: From Molecules to Black Holes. CoRR Ryan-Rhys Griffiths
2023	A*	`conf`	GAUCHE: A Library for Gaussian Processes in Chemistry. NeurIPS 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
2023	A*	`conf`	Mathematical Capabilities of ChatGPT. NeurIPS Simon Frieder, Luca Pinchetti, Alexis Chevalier, Ryan-Rhys Griffiths, Tommaso Salvatori, Thomas Lukasiewicz, Philipp Petersen, Julius Berner
2023	J	`jnl`	Mathematical Capabilities of ChatGPT. CoRR Simon Frieder, Luca Pinchetti, Ryan-Rhys Griffiths, Tommaso Salvatori, Thomas Lukasiewicz, Philipp Christian Petersen, Alexis Chevalier, Julius Berner
2022	J	`jnl`	Achieving robustness to aleatoric uncertainty with heteroscedastic Bayesian optimisation. Mach. Learn. Sci. Technol. Ryan-Rhys Griffiths, Alexander A. Aldrick, Miguel Garcia-Ortegon, Vidhi Lalchand, Alpha A. Lee
2022	—	`conf`	Extracting associations and meanings of objects depicted in artworks through bi-modal deep networks. Computer Vision and Image Analysis of Art Gregory Kell, Ryan-Rhys Griffiths, Anthony Bourached, David G. Stork
2022	J	`jnl`	Extracting associations and meanings of objects depicted in artworks through bi-modal deep networks. CoRR Gregory Kell, Ryan-Rhys Griffiths, Anthony Bourached, David G. Stork
2022	J	`jnl`	GAUCHE: A Library for Gaussian Processes in Chemistry. CoRR 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
2022	J	`jnl`	HEBO: An Empirical Study of Assumptions in Bayesian Optimisation. J. Artif. Intell. Res. 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
2021	J	`jnl`	Are We Forgetting about Compositional Optimisers in Bayesian Optimisation? J. Mach. Learn. Res. Antoine Grosnit, Alexander I. Cowen-Rivers, Rasul Tutunov, Ryan-Rhys Griffiths, Jun Wang, Haitham Bou-Ammar
2021	—	`conf`	Computational identification of significant actors in paintings through symbols and attributes. Computer Vision and Image Analysis of Art David G. Stork, Anthony Bourached, George H. Cann, Ryan-Rhys Griffiths
2021	J	`jnl`	Computational identification of significant actors in paintings through symbols and attributes. CoRR David G. Stork, Anthony Bourached, George H. Cann, Ryan-Rhys Griffiths
2021	J	`jnl`	Data Considerations in Graph Representation Learning for Supply Chain Networks. CoRR Ajmal Aziz, Edward Elson Kosasih, Ryan-Rhys Griffiths, Alexandra Brintrup
2021	J	`jnl`	Dataset Bias in the Natural Sciences: A Case Study in Chemical Reaction Prediction and Synthesis Design. CoRR Ryan-Rhys Griffiths, Philippe Schwaller, Alpha A. Lee
2021	J	`jnl`	Hierarchical Graph-Convolutional Variational AutoEncoding for Generative Modelling of Human Motion. CoRR Anthony Bourached, Robert J. Gray, Ryan-Rhys Griffiths, Ashwani Jha, Parashkev Nachev
2021	J	`jnl`	High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning. CoRR 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
2021	—	`conf`	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 Anthony Bourached, George H. Cann, Ryan-Rhys Griffiths, David G. Stork
2021	J	`jnl`	Recovery of underdrawings and ghost-paintings via style transfer by deep convolutional neural networks: A digital tool for art scholars. CoRR Anthony Bourached, George Cann, Ryan-Rhys Griffiths, David G. Stork
2021	—	`conf`	Resolution enhancement in the recovery of underdrawings via style transfer by generative adversarial deep neural networks. Computer Vision and Image Analysis of Art George H. Cann, Anthony Bourached, Ryan-Rhys Griffiths, David G. Stork
2021	J	`jnl`	Resolution enhancement in the recovery of underdrawings via style transfer by generative adversarial deep neural networks. CoRR George Cann, Anthony Bourached, Ryan-Rhys Griffiths, David G. Stork
2020	J	`jnl`	Are we Forgetting about Compositional Optimisers in Bayesian Optimisation? CoRR Antoine Grosnit, Alexander I. Cowen-Rivers, Rasul Tutunov, Ryan-Rhys Griffiths, Jun Wang, Haitham Bou-Ammar
2020	J	`jnl`	Gaussian Process Molecule Property Prediction with FlowMO. CoRR Henry B. Moss, Ryan-Rhys Griffiths
2020	J	`jnl`	Generative Model-Enhanced Human Motion Prediction. CoRR Anthony Bourached, Ryan-Rhys Griffiths, Robert J. Gray, Ashwani Jha, Parashkev Nachev
2019	J	`jnl`	Achieving Robustness to Aleatoric Uncertainty with Heteroscedastic Bayesian Optimisation. CoRR Ryan-Rhys Griffiths, Miguel Garcia-Ortegon, Alexander A. Aldrick, Alpha A. Lee
2019	A*	`conf`	Adaptive Sensor Placement for Continuous Spaces. ICML James A. Grant, Alexis Boukouvalas, Ryan-Rhys Griffiths, David S. Leslie, Sattar Vakili, Enrique Munoz de Cote
2019	J	`jnl`	Adaptive Sensor Placement for Continuous Spaces. CoRR James A. Grant, Alexis Boukouvalas, Ryan-Rhys Griffiths, David S. Leslie, Sattar Vakili, Enrique Munoz de Cote