Lars Andersen Bratholm
Lars Andersen Bratholm üzerinde doğrulanmış e-posta adresine sahip
Alıntı yapanlar
Alıntı yapanlar
FCHL revisited: Faster and more accurate quantum machine learning
AS Christensen, LA Bratholm, FA Faber, O Anatole von Lilienfeld
The Journal of chemical physics 152 (4), 044107, 2020
Training neural nets to learn reactive potential energy surfaces using interactive quantum chemistry in virtual reality
S Amabilino, LA Bratholm, SJ Bennie, AC Vaucher, M Reiher, ...
The Journal of Physical Chemistry A 123 (20), 4486-4499, 2019
QML: A Python toolkit for quantum machine learning
AS Christensen, FA Faber, B Huang, LA Bratholm, A Tkatchenko, ...
URL https://github. com/qmlcode/qml, 2017
Photutils: Photometry tools
L Bradley, B Sipocz, T Robitaille, E Tollerud, C Deil, Z Vinícius, K Barbary, ...
Astrophysics Source Code Library, ascl: 1609.011, 2016
IMPRESSION–prediction of NMR parameters for 3-dimensional chemical structures using machine learning with near quantum chemical accuracy
W Gerrard, LA Bratholm, MJ Packer, AJ Mulholland, DR Glowacki, ...
Chemical science 11 (2), 508-515, 2020
ProCS15: a DFT-based chemical shift predictor for backbone and Cβ atoms in proteins
AS Larsen, LA Bratholm, AS Christensen, M Channir, JH Jensen
PeerJ 3, e1344, 2015
Automated Fragmentation Polarizable Embedding Density Functional Theory (PE-DFT) Calculations of Nuclear Magnetic Resonance (NMR) Shielding Constants of Proteins with …
C Steinmann, LA Bratholm, JMH Olsen, J Kongsted
Journal of chemical theory and computation 13 (2), 525-536, 2017
Low dimensional representations along intrinsic reaction coordinates and molecular dynamics trajectories using interatomic distance matrices
SR Hare, LA Bratholm, DR Glowacki, BK Carpenter
Chemical science 10 (43), 9954-9968, 2019
Bayesian inference of protein structure from chemical shift data
LA Bratholm
Calculate root-mean-square deviation (RMSD) of two molecules using rotation
JC Kromann, L Bratholm
Xyz or Pdb Format: Charnley/Rmsd, 2019
Sonifying stochastic walks on biomolecular energy landscapes
RE Arbon, AJ Jones, LA Bratholm, T Mitchell, DR Glowacki
arXiv preprint arXiv:1803.05805, 2018
Protein structure refinement using a quantum mechanics-based chemical shielding predictor
LA Bratholm, JH Jensen
Chemical science 8 (3), 2061-2072, 2017
GitHub: Calculate RMSD for two XYZ structures
JC Kromann, L Bratholm
Training atomic neural networks using fragment-based data generated in virtual reality
S Amabilino, LA Bratholm, SJ Bennie, MB O’Connor, DR Glowacki
The Journal of Chemical Physics 153 (15), 154105, 2020
A community-powered search of machine learning strategy space to find NMR property prediction models
LA Bratholm, W Gerrard, B Anderson, S Bai, S Choi, L Dang, P Hanchar, ...
arXiv preprint arXiv:2008.05994, 2020
Protein Structure Validation and Refinement Using Chemical Shifts Derived from Quantum Mechanics
LA Bratholm
University of Copenhagen, Faculty of Science, Department of Chemistry, 2016
Computational Assignment of Chemical Shifts for Protein Residues
LA Bratholm
arXiv preprint arXiv:1311.3186, 2013
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