Huziel E. Sauceda
Title
Cited by
Cited by
Year
SchNet–A deep learning architecture for molecules and materials
KT Schütt, HE Sauceda, PJ Kindermans, A Tkatchenko, KR Müller
The Journal of Chemical Physics 148 (24), 241722, 2018
4762018
Machine learning of accurate energy-conserving molecular force fields
S Chmiela, A Tkatchenko, HE Sauceda, I Poltavsky, KT Schütt, KR Müller
Science advances 3 (5), e1603015, 2017
4592017
Schnet: A continuous-filter convolutional neural network for modeling quantum interactions
KT Schütt, PJ Kindermans, HE Sauceda, S Chmiela, A Tkatchenko, ...
arXiv preprint arXiv:1706.08566, 2017
2602017
Towards exact molecular dynamics simulations with machine-learned force fields
S Chmiela, HE Sauceda, KR Müller, A Tkatchenko
Nature communications 9 (1), 1-10, 2018
2182018
Vibrational properties of metal nanoparticles: Atomistic simulation and comparison with time-resolved investigation
HE Sauceda, D Mongin, P Maioli, A Crut, M Pellarin, N Del Fatti, F Vallée, ...
The Journal of Physical Chemistry C 116 (47), 25147-25156, 2012
652012
sGDML: Constructing accurate and data efficient molecular force fields using machine learning
S Chmiela, HE Sauceda, I Poltavsky, KR Müller, A Tkatchenko
Computer Physics Communications 240, 38-45, 2019
542019
Molecular force fields with gradient-domain machine learning: Construction and application to dynamics of small molecules with coupled cluster forces
HE Sauceda, S Chmiela, I Poltavsky, KR Müller, A Tkatchenko
The Journal of chemical physics 150 (11), 114102, 2019
392019
Size and shape dependence of the vibrational spectrum and low-temperature specific heat of Au nanoparticles
HE Sauceda, F Salazar, LA Pérez, IL Garzón
The Journal of Physical Chemistry C 117 (47), 25160-25168, 2013
362013
Advances in Neural Information Processing Systems 30
K Schütt, PJ Kindermans, HE Sauceda, S Chmiela, A Tkatchenko, ...
Guyon, I., Luxburg, UV, Bengio, S., Wallach, H., Fergus, R., Vishwanathan, S …, 2017
302017
Mechanical vibrations of atomically defined metal clusters: From nano-to molecular-size oscillators
P Maioli, T Stoll, HE Sauceda, I Valencia, A Demessence, F Bertorelle, ...
Nano letters 18 (11), 6842-6849, 2018
282018
Structural determination of metal nanoparticles from their vibrational (phonon) density of states
HE Sauceda, IL Garzón
The Journal of Physical Chemistry C 119 (20), 10876-10880, 2015
282015
Vibrational Spectrum, Caloric Curve, Low-Temperature Heat Capacity, and Debye Temperature of Sodium Clusters: The Na139+ Case
HE Sauceda, JJ Pelayo, F Salazar, LA Pérez, IL Garzón
The Journal of Physical Chemistry C 117 (21), 11393-11398, 2013
182013
Machine learning force fields
OT Unke, S Chmiela, HE Sauceda, M Gastegger, I Poltavsky, KT Schütt, ...
Chemical Reviews, 2020
102020
Construction of machine learned force fields with quantum chemical accuracy: applications and chemical insights
HE Sauceda, S Chmiela, I Poltavsky, KR Müller, A Tkatchenko
arXiv preprint arXiv:1909.08565, 2019
102019
Vibrational properties and specific heat of core–shell Ag–Au icosahedral nanoparticles
HE Sauceda, IL Garzón
Physical Chemistry Chemical Physics 17 (42), 28054-28059, 2015
92015
Dynamical strengthening of covalent and non-covalent molecular interactions by nuclear quantum effects at finite temperature
HE Sauceda, V Vassilev-Galindo, S Chmiela, KR Müller, A Tkatchenko
Nature Communications 12 (1), 1-10, 2021
62021
Molecular force fields with gradient-domain machine learning (GDML): Comparison and synergies with classical force fields
HE Sauceda, M Gastegger, S Chmiela, KR Müller, A Tkatchenko
The Journal of Chemical Physics 153 (12), 124109, 2020
52020
Accurate molecular dynamics enabled by efficient physically constrained machine learning approaches
S Chmiela, HE Sauceda, A Tkatchenko, KR Müller
Machine Learning Meets Quantum Physics, 129-154, 2020
32020
Modeling molecular spectra with interpretable atomistic neural networks
M Gastegger, K Schütt, H Sauceda, KR Müller, A Tkatchenko
APS March Meeting Abstracts 2019, E32. 007, 2019
22019
Machine Learning of Accurate Energy-Conserving Molecular Force Fields.(May): 1–6, 2016
S Chmiela, A Tkatchenko, HE Sauceda, I Poltavsky, KT Schütt, KR Müller
ISSN, 0
2
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Articles 1–20