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2007.05320
Cited By
Machine learning for electronically excited states of molecules
Chemical Reviews (Chem. Rev.), 2020
10 July 2020
Julia Westermayr
P. Marquetand
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Papers citing
"Machine learning for electronically excited states of molecules"
26 / 26 papers shown
Ab-initio simulation of excited-state potential energy surfaces with transferable deep quantum Monte Carlo
Zeno Schätzle
P. Szabó
Alice Cuzzocrea
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25 Mar 2025
A Framework for Finding Local Saddle Points in Two-Player Zero-Sum Black-Box Games
Shubhankar Agarwal
Hamzah I. Khan
Sandeep Chinchali
David Fridovich-Keil
386
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0
23 Mar 2025
A practical guide to machine learning interatomic potentials -- Status and future
Current opinion in solid state & materials science (OSSMS), 2025
Ryan Jacobs
D. Morgan
Siamak Attarian
Jun Meng
Chen Shen
...
K. J. Schmidt
So Takamoto
Aidan Thompson
Julia Westermayr
Brandon M. Wood
456
143
0
12 Mar 2025
Investigating Data Hierarchies in Multifidelity Machine Learning for Excitation Energies
Journal of Chemical Theory and Computation (JCTC), 2024
Vivin Vinod
Peter Zaspel
383
4
0
15 Oct 2024
Assessing Non-Nested Configurations of Multifidelity Machine Learning for Quantum-Chemical Properties
Vivin Vinod
Peter Zaspel
AI4CE
244
5
0
24 Jul 2024
CheMFi: A Multifidelity Dataset of Quantum Chemical Properties of Diverse Molecules
Vivin Vinod
Peter Zaspel
267
8
0
20 Jun 2024
Electronic excited states from physically-constrained machine learning
ACS Central Science (ACS Cent. Sci.), 2023
Edoardo Cignoni
Divya Suman
Jigyasa Nigam
Lorenzo Cupellini
B. Mennucci
Michele Ceriotti
366
27
0
01 Nov 2023
Accelerating Electronic Stopping Power Predictions by 10 Million Times with a Combination of Time-Dependent Density Functional Theory and Machine Learning
npj Computational Materials (npj Comput Mater), 2023
Logan T. Ward
Ben Blaiszik
Cheng-Wei Lee
Troy Martin
Ian Foster
A. Schleife
352
9
0
01 Nov 2023
Multi-Fidelity Machine Learning for Excited State Energies of Molecules
Journal of Chemical Theory and Computation (JCTC), 2023
Vivin Vinod
Sayan Maity
Peter Zaspel
Ulrich Kleinekathöfer
AI4CE
259
13
0
18 May 2023
Robust, randomized preconditioning for kernel ridge regression
Mateo Díaz
Ethan N. Epperly
Zachary Frangella
J. Tropp
R. Webber
650
19
0
24 Apr 2023
Towards a Foundation Model for Neural Network Wavefunctions
Michael Scherbela
Leon Gerard
Philipp Grohs
326
11
0
17 Mar 2023
Lifelong Machine Learning Potentials
Journal of Chemical Theory and Computation (JCTC), 2023
Marco Eckhoff
Markus Reiher
411
34
0
10 Mar 2023
HOAX: A Hyperparameter Optimization Algorithm Explorer for Neural Networks
Molecular Physics (Mol. Phys.), 2023
Albert S. Thie
M. Menger
S. Faraji
247
0
0
01 Feb 2023
Low-cost machine learning approach to the prediction of transition metal phosphor excited state properties
Gianmarco G. Terrones
Chenru Duan
Aditya Nandy
Heather J. Kulik
264
0
0
18 Sep 2022
Transition1x -- a Dataset for Building Generalizable Reactive Machine Learning Potentials
Scientific Data (Sci Data), 2022
Mathias Jacob Schreiner
Arghya Bhowmik
Tejs Vegge
Jonas Busk
Ole Winther
282
104
0
25 Jul 2022
NeuralNEB -- Neural Networks can find Reaction Paths Fast
Mathias Jacob Schreiner
Arghya Bhowmik
Tejs Vegge
Peter Bjørn Jørgensen
Ole Winther
389
40
0
20 Jul 2022
Electronic-structure properties from atom-centered predictions of the electron density
Journal of Chemical Theory and Computation (JCTC), 2022
Andrea Grisafi
Alan M Lewis
M. Rossi
Michele Ceriotti
295
22
0
28 Jun 2022
Accurate Machine Learned Quantum-Mechanical Force Fields for Biomolecular Simulations
Oliver T. Unke
M. Stohr
Stefan Ganscha
Thomas Unterthiner
Hartmut Maennel
...
Daniel Ahlin
M. Gastegger
L. M. Sandonas
A. Tkatchenko
Klaus-Robert Muller
AI4CE
274
19
0
17 May 2022
SELFIES and the future of molecular string representations
Patterns (Patterns), 2022
Mario Krenn
Qianxiang Ai
Senja Barthel
Nessa Carson
Angelo Frei
...
Andrew Wang
Andrew D. White
Adamo Young
Rose Yu
A. Aspuru‐Guzik
381
234
0
31 Mar 2022
Electronic excited states in deep variational Monte Carlo
Nature Communications (Nat Commun), 2022
M. Entwistle
Zeno Schätzle
P. A. Erdman
Jan Hermann
Frank Noé
348
70
0
17 Mar 2022
Excited state, non-adiabatic dynamics of large photoswitchable molecules using a chemically transferable machine learning potential
Nature Communications (Nat Commun), 2021
Simon Axelrod
E. Shakhnovich
Rafael Gómez-Bombarelli
312
66
0
10 Aug 2021
Solving the electronic Schrödinger equation for multiple nuclear geometries with weight-sharing deep neural networks
Nature Computational Science (Nat. Comput. Sci.), 2021
Michael Scherbela
Rafael Reisenhofer
Leon Gerard
P. Marquetand
Philipp Grohs
273
62
0
18 May 2021
Accurate Prediction of Free Solvation Energy of Organic Molecules via Graph Attention Network and Message Passing Neural Network from Pairwise Atomistic Interactions
Ramin Ansari
Amirata Ghorbani
221
2
0
15 Apr 2021
Automated and Autonomous Experiment in Electron and Scanning Probe Microscopy
Sergei V. Kalinin
M. Ziatdinov
Jacob D. Hinkle
S. Jesse
Ayana Ghosh
K. Kelley
A. Lupini
B. Sumpter
Rama K Vasudevan
251
3
0
22 Mar 2021
Machine Learning Force Fields
Oliver T. Unke
Stefan Chmiela
H. E. Sauceda
M. Gastegger
I. Poltavsky
Kristof T. Schütt
A. Tkatchenko
K. Müller
AI4CE
409
1,296
0
14 Oct 2020
Deep Learning for UV Absorption Spectra with SchNarc: First Steps Towards Transferability in Chemical Compound Space
Journal of Chemical Physics (JCP), 2020
Julia Westermayr
P. Marquetand
265
60
0
15 Jul 2020
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