Huziel E. Sauceda
Huziel E. Sauceda
Verified email at fhi-berlin.mpg.de - Homepage
Title
Cited by
Cited by
Year
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
3152017
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
2632018
Schnet: A continuous-filter convolutional neural network for modeling quantum interactions
K Schütt, PJ Kindermans, HES Felix, S Chmiela, A Tkatchenko, KR Müller
Advances in neural information processing systems, 991-1001, 2017
1652017
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
1232018
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
592012
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
322013
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
252019
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
242015
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
202019
Advances in Neural Information Processing Systems 30
K Schütt, PJ Kindermans, HE Sauceda Felix, S Chmiela, A Tkatchenko, ...
Guyon, I., Luxburg, UV, Bengio, S., Wallach, H., Fergus, R., Vishwanathan, S …, 2017
192017
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
162013
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
152018
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
82015
SchNet: A continuous-filter convolutional neural network for modeling quantum interactions. NIPS 30
KT Schütt, PJ Kindermans, HE Sauceda, S Chmiela, A Tkatchenko, ...
Zeng, Tahaei, Chen, Meister, Shah, Gupta, Jalal, Arvaniti, Zimmerer …, 2017
62017
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
52019
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
22020
Modeling molecular spectra with interpretable atomistic neural networks
M Gastegger, K Schütt, H Sauceda, KR Müller, A Tkatchenko
APS 2019, E32. 007, 2019
22019
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
arXiv preprint arXiv:2006.10578, 2020
2020
Nuclear quantum delocalization enhances non-covalent intramolecular interactions: A machine learning and path integral molecular dynamics study
H Sauceda, V Vassilev Galindo, S Chmiela, KR Müller, A Tkatchenko
Bulletin of the American Physical Society 65, 2020
2020
Addressing the Elephant in the Room: Uncertainties in Physical Predictions From Machine-Learned Force Fields
S Chmiela, H Sauceda, KR Müller, A Tkatchenko
Bulletin of the American Physical Society 65, 2020
2020
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