Gareth Conduit

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Tom WhiteheadIntellegensDirección de correo verificada de intellegens.ai
Howard StoneUniversity of CambridgeDirección de correo verificada de cam.ac.uk
Benjamin D SimonsUniversity of CambridgeDirección de correo verificada de cam.ac.uk
Benedict W. J. IrwinCHARM TherapeuticsDirección de correo verificada de charmtx.com
Jin ZhaoNanjing University of Posts and TelecommunicationsDirección de correo verificada de njupt.edu.cn
Qingyu YanProfessor of Materials Science and Engineering, Nanyang Technological UniversityDirección de correo verificada de ntu.edu.sg
andrew g. greenUniversity College LondonDirección de correo verificada de ucl.ac.uk
Pascal BugnionCavendish Laboratory, Cambridge UniversityDirección de correo verificada de cam.ac.uk
Pablo López RíosMax-Planck Institute for Solid State ReseachDirección de correo verificada de fkf.mpg.de
Zhi Wei SehInstitute of Materials Research and Engineering, A*STARDirección de correo verificada de imre.a-star.edu.sg
Man-Fai Ng, AndyInstitute of High Performance ComputingDirección de correo verificada de ihpc.a-star.edu.sg
Nicholas G JonesUniversity of CambridgeDirección de correo verificada de cam.ac.uk
Neil DrummondLancaster UniversityDirección de correo verificada de lancaster.ac.uk
David Fairen-Jimenez | ORCID: 0000-...Dept. of Chemical Engineering and Biotechnology, University of CambridgeDirección de correo verificada de cam.ac.uk
Peyman Z. MoghadamAssociate Professor, University College LondonDirección de correo verificada de ucl.ac.uk
Jelle WiemeCenter for Molecular Modeling, Ghent UniversityDirección de correo verificada de ugent.be
Sven M.J. RoggeAssociate Research Professor, Center for Molecular Modeling, Ghent UniversityDirección de correo verificada de UGent.be
Diego A. Gomez-GualdronAssociate Professor, Colorado School of MinesDirección de correo verificada de mines.edu
Aurélia LiPhD, University of CambridgeDirección de correo verificada de cam.ac.uk
Noushin MoharramiNewcastle UniversityDirección de correo verificada de twi.co.uk

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Gareth Conduit

University of Cambridge

Dirección de correo verificada de cam.ac.uk - Página principal

Machine learning Condensed matter physics


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
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	566	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	258	2019
Inhomogeneous phase formation on the border of itinerant ferromagnetism GJ Conduit, AG Green, BD Simons Physical review letters 103 (20), 207201, 2009	233	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	151	2017
OPTIMADE, an API for exchanging materials data CW Andersen, R Armiento, E Blokhin, GJ Conduit, S Dwaraknath, ... Scientific data 8 (1), 217, 2021	96	2021
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	89	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—Atomic, Molecular, and Optical Physics 77 (5), 053617, 2008	83	2008
Materials data validation and imputation with an artificial neural network PC Verpoort, P MacDonald, GJ Conduit Computational Materials Science 147, 176-185, 2018	81	2018
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	72	2019
Strategies for improving the efficiency of quantum Monte Carlo calculations RM Lee, GJ Conduit, N Nemec, P López Ríos, ND Drummond Physical Review E—Statistical, Nonlinear, and Soft Matter Physics 83 (6 …, 2011	70	2011
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	65	2020
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—Atomic, Molecular, and Optical Physics 79 (5), 053606, 2009	64	2009
Ferromagnetic spin correlations in a few-fermion system PO Bugnion, GJ Conduit Physical Review A—Atomic, Molecular, and Optical Physics 87 (6), 060502, 2013	52	2013
Quantum order-by-disorder in strongly correlated metals AG Green, G Conduit, F Kruger Annual Review of Condensed Matter Physics 9, 59-77, 2018	49	2018
Itinerant ferromagnetism in a two-dimensional atomic gas GJ Conduit Physical Review A—Atomic, Molecular, and Optical Physics 82 (4), 043604, 2010	47	2010
Line of Dirac monopoles embedded in a Bose-Einstein condensate GJ Conduit Physical Review A—Atomic, Molecular, and Optical Physics 86 (2), 021605, 2012	46	2012
Formulation and manufacturing optimization of lithium-ion graphite-based electrodes via machine learning SX Drakopoulos, A Gholamipour-Shirazi, P MacDonald, RC Parini, ... Cell Reports Physical Science 2 (12), 2021	41	2021
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	40	2018
Prediction of in vivo pharmacokinetic parameters and time–exposure curves in rats using machine learning from the chemical structure O Obrezanova, A Martinsson, T Whitehead, S Mahmoud, A Bender, ... Molecular pharmaceutics 19 (5), 1488-1504, 2022	39	2022

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