Ryan-Rhys Griffiths

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Simon FriederUniversity of OxfordVerified email at cs.ox.ac.uk
Henry B MossEarly Career Fellow, University of CambridgeVerified email at cam.ac.uk
Haitham Bou-AmmarRL-Team Leader, BO-Team Leader, MAS-Team Leader @ Huawei London & H. Assistant Professor @ UCLVerified email at huawei.com
Jun WangProfessor, Computer Science, University College LondonVerified email at cs.ucl.ac.uk
Arian JamasbSenior ML Scientist, Prescient DesignVerified email at roche.com
José Miguel Hernández-LobatoProfessor of Machine Learning, University of CambridgeVerified email at cam.ac.uk
Jan PetersProfessor for Intelligent Autonomous Systems/TU Darmstadt, Dept. Head/German AI Research Center DFKIVerified email at ias.tu-darmstadt.de
David G. StorkAdjunct Professor, Stanford UniversityVerified email at alum.mit.edu
Philippe SchwallerAssistant Professor, Laboratory of Artificial Chemical Intelligence - EPFLVerified email at epfl.ch
Alpha LeeUniversity of CambridgeVerified email at cam.ac.uk
Sattar VakiliMediaTek ResearchVerified email at mtkresearch.com
Enrique Munoz de CoteProfessor of Computer Science at INAOE; CTO @ Mutable Tactics; past: Director at SecondmindVerified email at mutabletactics.ai
Bingqing ChengAssistant Professor at University of California, BerkeleyVerified email at berkeley.edu
Dan WilkinsResearch Scientist, Stanford UniversityVerified email at stanford.edu
David S. LeslieProfessor of Statistical Learning, Lancaster UniversityVerified email at lancaster.ac.uk
Vidhi LalchandBroad Institute of MIT & Harvard; MIT; University of CambridgeVerified email at mit.edu
Erin Amira KaraMITVerified email at mit.edu
Alexis BoukouvalasResearch Engineering Team Lead at DeepMind
Jian Tang (唐建）Associate Professor, Mila-Quebec AI Institute, HEC Montréal, Canada CIFAR AI ChairVerified email at hec.ca
Alan Aspuru-GuzikProfessor of Chemistry and Computer Science, University of Toronto (starting July 1, 2018)Verified email at utoronto.ca

Ryan-Rhys Griffiths

FutureHouse

Verified email at futurehouse.org - Homepage

Machine Learning Physics Bayesian Optimization AI for Science Large Language Models


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Mathematical Capabilities of ChatGPT S Frieder, L Pinchetti, RR Griffiths, T Salvatori, T Lukasiewicz, P Petersen, ... Advances in Neural Information Processing Systems 36, 2024	596*	2024
Constrained Bayesian Optimization for Automatic Chemical Design using Variational Autoencoders RR Griffiths, JM Hernández-Lobato Chemical Science 11 (2), 577-586, 2020	462	2020
HEBO: Pushing the Limits of Sample-Efficient Hyper-Parameter Optimisation AI Cowen-Rivers, W Lyu, R Tutunov, Z Wang, A Grosnit, RR Griffiths, ... Journal of Artificial Intelligence Research 74, 1269-1349, 2022	183*	2022
Mapping Materials and Molecules B Cheng, RR Griffiths, S Wengert, C Kunkel, T Stenczel, B Zhu, ... Accounts of Chemical Research 53 (9), 1981-1991, 2020	109	2020
High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning RR Griffiths, A Grosnit, R Tutunov, AM Maraval, AI Cowen-Rivers, ... arXiv preprint arXiv:2106.03609, 2021	64*	2021
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	54*	2024
Data-Driven Discovery of Molecular Photoswitches with Multioutput Gaussian Processes RR Griffiths, JL Greenfield, AR Thawani, AR Jamasb, HB Moss, ... Chemical Science 13, 13541 - 13551, 2022	53*	2022
Achieving Robustness to Aleatoric Uncertainty with Heteroscedastic Bayesian Optimisation RR Griffiths, AA Aldrick, M Garcia-Ortegon, V Lalchand Machine Learning: Science and Technology 3 (1), 015004, 2021	43*	2021
Gaussian Process Molecule Property Prediction with FlowMO HB Moss, RR Griffiths NeurIPS 2020: Workshop on ML4Molecules, 2020	30*	2020
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 2021, 2021	24*	2021
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	23	2021
Generative Model‐Enhanced Human Motion Prediction A Bourached, RR Griffiths, R Gray, A Jha, P Nachev Applied AI Letters 3 (2), e63, 2022	20	2022
Dataset Bias in the Natural Sciences: A Case Study in Chemical Reaction Prediction and Synthesis Design RR Griffiths, P Schwaller, AA Lee arXiv preprint arXiv:2105.02637, 2021	20*	2021
Data Considerations in Graph Representation Learning for Supply Chain Networks A Aziz, EE Kosasih, RR Griffiths, A Brintrup ICML 2021: Workshop on ML4Data, 2021	19	2021
Adaptive Sensor Placement for Continuous Spaces JA Grant, A Boukouvalas, RR Griffiths, DS Leslie, S Vakili, EM De Cote ICML 2019, 2019	19	2019
Bayesian Optimisation for Additive Screening and Yield Improvements–Beyond One-Hot Encoding B Ranković, RR Griffiths, HB Moss, P Schwaller Digital Discovery, 2024	17*	2024
Are We Forgetting about Compositional Optimisers in Bayesian Optimisation? A Grosnit, AI Cowen-Rivers, R Tutunov, RR Griffiths, J Wang, ... Journal of Machine Learning Research, 22(160), 1-78., 2021	17	2021
Computational Identification of Significant Actors in Paintings through Symbols and Attributes DG Stork, A Bourached, GH Cann, RR Griffiths Electronic Imaging 2021, 2021	13	2021
Resolution Enhancement in the Recovery of Underdrawings via Style Transfer by Generative Adversarial Deep Neural Networks G Cann, A Bourached, RR Griffiths, D Stork Electronic Imaging 2021, 2021	9*	2021
High-Dimensional Bayesian Optimization with Invariance E Verma, S Chakraborty, RR Griffiths ICML Workshop on Adaptive Experimental Design and Active Learning, 2022	8*	2022

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