Gareth Conduit

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Tom WhiteheadIntellegensVerified email at intellegens.ai
Howard StoneUniversity of CambridgeVerified email at cam.ac.uk
Benjamin D SimonsUniversity of CambridgeVerified email at cam.ac.uk
Benedict W. J. IrwinCHARM TherapeuticsVerified email at charmtx.com
andrew g. greenUniversity College LondonVerified email at ucl.ac.uk
Jin ZhaoNanjing University of Posts and TelecommunicationsVerified email at njupt.edu.cn
Qingyu YanProfessor of Materials Science and Engineering, Nanyang Technological UniversityVerified email at ntu.edu.sg
Pascal BugnionCavendish Laboratory, Cambridge UniversityVerified email at cam.ac.uk
Pablo López RíosMax-Planck Institute for Solid State ReseachVerified email at fkf.mpg.de
Zhi Wei SehInstitute of Materials Research and Engineering, A*STARVerified email at imre.a-star.edu.sg
Man-Fai Ng, AndyInstitute of High Performance ComputingVerified email at ihpc.a-star.edu.sg
Nicholas G JonesUniversity of CambridgeVerified email at cam.ac.uk
Neil DrummondLancaster UniversityVerified email at lancaster.ac.uk
Bartomeu MonserratDepartment of Materials Science and Metallurgy, Cambridge UniversityVerified email at cam.ac.uk
David Fairen-Jimenez | ORCID: 0000-...Dept. of Chemical Engineering and Biotechnology, University of CambridgeVerified email at cam.ac.uk
Peyman Z. MoghadamAssociate Professor, University College LondonVerified email at ucl.ac.uk
Jelle WiemeCenter for Molecular Modeling, Ghent UniversityVerified email at ugent.be
Sven M.J. RoggeAssociate Research Professor, Center for Molecular Modeling, Ghent UniversityVerified email at UGent.be
Diego A. Gomez-GualdronAssociate Professor, Colorado School of MinesVerified email at mines.edu
Aurélia LiPhD, University of CambridgeVerified email at cam.ac.uk

Gareth Conduit

University of Cambridge

Verified email at cam.ac.uk - Homepage

Machine learning Condensed matter physics


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Predicting the state of charge and health of batteries using data-driven machine learning MF Ng, J Zhao, Q Yan, GJ Conduit, ZW Seh Nature Machine Intelligence 2 (3), 161-170, 2020	456	2020
Structure-mechanical stability relations of metal-organic frameworks via machine learning PZ Moghadam, SMJ Rogge, A Li, CM Chow, J Wieme, N Moharrami, ... Matter 1 (1), 219-234, 2019	222	2019
Inhomogeneous phase formation on the border of itinerant ferromagnetism GJ Conduit, AG Green, BD Simons Physical review letters 103 (20), 207201, 2009	210	2009
Design of a nickel-base superalloy using a neural network BD Conduit, NG Jones, HJ Stone, GJ Conduit Materials & Design 131, 358-365, 2017	130	2017
Grain growth behaviour during near-γ′ solvus thermal exposures in a polycrystalline nickel-base superalloy DM Collins, BD Conduit, HJ Stone, MC Hardy, GJ Conduit, RJ Mitchell Acta materialia 61 (9), 3378-3391, 2013	81	2013
Superfluidity at the BEC-BCS crossover in two-dimensional Fermi gases with population and mass imbalance GJ Conduit, PH Conlon, BD Simons Physical Review A 77 (5), 053617, 2008	81	2008
OPTIMADE, an API for exchanging materials data CW Andersen, R Armiento, E Blokhin, GJ Conduit, S Dwaraknath, ... Scientific data 8 (1), 217, 2021	80	2021
Materials data validation and imputation with an artificial neural network PC Verpoort, P MacDonald, GJ Conduit Computational Materials Science 147, 176-185, 2018	74	2018
Strategies for improving the efficiency of quantum Monte Carlo calculations RM Lee, GJ Conduit, N Nemec, PL Ríos, ND Drummond Physical Review E 83 (6), 066706, 2011	71	2011
Repulsive atomic gas in a harmonic trap on the border of itinerant ferromagnetism GJ Conduit, BD Simons Physical review letters 103 (20), 200403, 2009	64	2009
Itinerant ferromagnetism in an atomic Fermi gas: Influence of population imbalance GJ Conduit, BD Simons Physical Review A 79 (5), 053606, 2009	63	2009
Imputation of assay bioactivity data using deep learning TM Whitehead, BWJ Irwin, P Hunt, MD Segall, GJ Conduit Journal of chemical information and modeling 59 (3), 1197-1204, 2019	62	2019
Practical applications of deep learning to impute heterogeneous drug discovery data BWJ Irwin, JR Levell, TM Whitehead, MD Segall, GJ Conduit Journal of Chemical Information and Modeling 60 (6), 2848-2857, 2020	57	2020
Ferromagnetic spin correlations in a few-fermion system PO Bugnion, GJ Conduit Physical Review A 87 (6), 060502, 2013	53	2013
Line of Dirac monopoles embedded in a Bose-Einstein condensate GJ Conduit Physical Review A 86 (2), 021605, 2012	45	2012
Quantum order-by-disorder in strongly correlated metals AG Green, G Conduit, F Kruger Annual Review of Condensed Matter Physics 9, 59-77, 2018	44	2018
Itinerant ferromagnetism in a two-dimensional atomic gas GJ Conduit Physical Review A 82 (4), 043604, 2010	43	2010
Itinerant ferromagnetism in an interacting Fermi gas with mass imbalance CW von Keyserlingk, GJ Conduit Physical Review A 83 (5), 053625, 2011	36	2011
Probabilistic design of a molybdenum-base alloy using a neural network BD Conduit, NG Jones, HJ Stone, GJ Conduit Scripta Materialia 146, 82-86, 2018	34	2018
Probabilistic neural network identification of an alloy for direct laser deposition BD Conduit, T Illston, S Baker, DV Duggappa, S Harding, HJ Stone, ... Materials & Design 168, 107644, 2019	31	2019

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