John L.A. Gardner 个人学术档案

2022202320241 27 37

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Volker L. DeringerUniversity of Oxford在 chem.ox.ac.uk 的电子邮件经过验证
Joe D. MorrowPhD Student, University of Oxford在 queens.ox.ac.uk 的电子邮件经过验证
Zoe Faure BeaulieuPhD Candidate in Computational Discovery, University of Oxford在 stcatz.ox.ac.uk 的电子邮件经过验证
Andrew GoodwinProfessor of Materials Chemistry, University of Oxford在 chem.ox.ac.uk 的电子邮件经过验证
Thomas NicholasDPhil in Inorganic Chemistry, University of Oxford在 chem.ox.ac.uk 的电子邮件经过验证
William BarfordUniversity of Oxford在 chem.ox.ac.uk 的电子邮件经过验证
Chiheb Ben MahmoudPostdoctoral Research Associate, University of Oxford在 chem.ox.ac.uk 的电子邮件经过验证

John L.A. Gardner

Machine Learning for Science, University of Oxford

在 chem.ox.ac.uk 的电子邮件经过验证 - 首页


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
How to validate machine-learned interatomic potentials JD Morrow, JLA Gardner, VL Deringer The Journal of chemical physics 158 (12), 2023	44	2023
Synthetic data enable experiments in atomistic machine learning JLA Gardner, ZF Beaulieu, VL Deringer Digital Discovery 2 (3), 651-662, 2023	9	2023
Synthetic pre-training for neural-network interatomic potentials JLA Gardner, KT Baker, VL Deringer Machine Learning: Science and Technology 5 (1), 015003, 2024	6	2024
Coarse-grained versus fully atomistic machine learning for zeolitic imidazolate frameworks ZF Beaulieu, TC Nicholas, JLA Gardner, AL Goodwin, VL Deringer Chemical Communications 59 (76), 11405-11408, 2023	4	2023
Using spectroscopy to probe relaxation, decoherence, and localization of photoexcited states in π-conjugated polymers W Barford, JLA Gardner, JR Mannouch Faraday Discussions 221, 281-298, 2020	2	2020
Data as the next challenge in atomistic machine learning C Ben Mahmoud, JLA Gardner, VL Deringer Nature Computational Science, 1-4, 2024		2024

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