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Gareth Conduit
Tytuł
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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
6182020
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
2702019
Inhomogeneous phase formation on the border of itinerant ferromagnetism
GJ Conduit, AG Green, BD Simons
Physical review letters 103 (20), 207201, 2009
2342009
Design of a nickel-base superalloy using a neural network
BD Conduit, NG Jones, HJ Stone, GJ Conduit
Materials & Design 131, 358-365, 2017
1582017
OPTIMADE, an API for exchanging materials data
CW Andersen, R Armiento, E Blokhin, GJ Conduit, S Dwaraknath, ...
Scientific data 8 (1), 217, 2021
1012021
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
922013
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
842008
Materials data validation and imputation with an artificial neural network
PC Verpoort, P MacDonald, GJ Conduit
Computational Materials Science 147, 176-185, 2018
822018
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
732019
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
712011
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
672020
Repulsive atomic gas in a harmonic trap on the border of itinerant ferromagnetism
GJ Conduit, BD Simons
Physical review letters 103 (20), 200403, 2009
642009
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
642009
Ferromagnetic spin correlations in a few-fermion system
PO Bugnion, GJ Conduit
Physical Review A—Atomic, Molecular, and Optical Physics 87 (6), 060502, 2013
532013
Quantum order-by-disorder in strongly correlated metals
AG Green, G Conduit, F Kruger
Annual Review of Condensed Matter Physics 9, 59-77, 2018
502018
Itinerant ferromagnetism in a two-dimensional atomic gas
GJ Conduit
Physical Review A—Atomic, Molecular, and Optical Physics 82 (4), 043604, 2010
492010
Line of Dirac monopoles embedded in a Bose-Einstein condensate
GJ Conduit
Physical Review A—Atomic, Molecular, and Optical Physics 86 (2), 021605, 2012
462012
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
422022
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
412021
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
412018
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