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Machine learning for electronically excited states of molecules

Machine learning for electronically excited states of molecules

10 July 2020
Julia Westermayr
P. Marquetand
ArXivPDFHTML

Papers citing "Machine learning for electronically excited states of molecules"

28 / 28 papers shown
Title
Ab-initio simulation of excited-state potential energy surfaces with transferable deep quantum Monte Carlo
Ab-initio simulation of excited-state potential energy surfaces with transferable deep quantum Monte Carlo
Zeno Schätzle
P. Szabó
Alice Cuzzocrea
Frank Noé
40
0
0
25 Mar 2025
A Framework for Finding Local Saddle Points in Two-Player Zero-Sum Black-Box Games
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
41
0
0
23 Mar 2025
A practical guide to machine learning interatomic potentials -- Status and future
Ryan Jacobs
D. Morgan
Siamak Attarian
Jun Meng
Chen Shen
...
K. J. Schmidt
So Takamoto
Aidan Thompson
Julia Westermayr
Brandon M. Wood
59
4
0
12 Mar 2025
Investigating Data Hierarchies in Multifidelity Machine Learning for Excitation Energies
Investigating Data Hierarchies in Multifidelity Machine Learning for Excitation Energies
Vivin Vinod
Peter Zaspel
21
0
0
15 Oct 2024
Assessing Non-Nested Configurations of Multifidelity Machine Learning
  for Quantum-Chemical Properties
Assessing Non-Nested Configurations of Multifidelity Machine Learning for Quantum-Chemical Properties
Vivin Vinod
Peter Zaspel
AI4CE
31
3
0
24 Jul 2024
CheMFi: A Multifidelity Dataset of Quantum Chemical Properties of
  Diverse Molecules
CheMFi: A Multifidelity Dataset of Quantum Chemical Properties of Diverse Molecules
Vivin Vinod
Peter Zaspel
29
4
0
20 Jun 2024
Electronic excited states from physically-constrained machine learning
Electronic excited states from physically-constrained machine learning
Edoardo Cignoni
Divya Suman
Jigyasa Nigam
Lorenzo Cupellini
B. Mennucci
Michele Ceriotti
31
15
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
Accelerating Electronic Stopping Power Predictions by 10 Million Times with a Combination of Time-Dependent Density Functional Theory and Machine Learning
Logan T. Ward
Ben Blaiszik
Cheng-Wei Lee
Troy Martin
Ian Foster
A. Schleife
11
4
0
01 Nov 2023
Multi-Fidelity Machine Learning for Excited State Energies of Molecules
Multi-Fidelity Machine Learning for Excited State Energies of Molecules
Vivin Vinod
Sayan Maity
Peter Zaspel
Ulrich Kleinekathöfer
AI4CE
15
7
0
18 May 2023
Robust, randomized preconditioning for kernel ridge regression
Robust, randomized preconditioning for kernel ridge regression
Mateo Díaz
Ethan N. Epperly
Zachary Frangella
J. Tropp
R. Webber
36
11
0
24 Apr 2023
Towards a Foundation Model for Neural Network Wavefunctions
Towards a Foundation Model for Neural Network Wavefunctions
Michael Scherbela
Leon Gerard
Philipp Grohs
32
8
0
17 Mar 2023
Lifelong Machine Learning Potentials
Lifelong Machine Learning Potentials
Marco Eckhoff
Markus Reiher
62
20
0
10 Mar 2023
HOAX: A Hyperparameter Optimization Algorithm Explorer for Neural
  Networks
HOAX: A Hyperparameter Optimization Algorithm Explorer for Neural Networks
Albert S. Thie
M. Menger
S. Faraji
22
0
0
01 Feb 2023
Low-cost machine learning approach to the prediction of transition metal
  phosphor excited state properties
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
13
0
0
18 Sep 2022
Transition1x -- a Dataset for Building Generalizable Reactive Machine
  Learning Potentials
Transition1x -- a Dataset for Building Generalizable Reactive Machine Learning Potentials
M. Schreiner
Arghya Bhowmik
Tejs Vegge
Jonas Busk
Ole Winther
21
62
0
25 Jul 2022
NeuralNEB -- Neural Networks can find Reaction Paths Fast
NeuralNEB -- Neural Networks can find Reaction Paths Fast
M. Schreiner
Arghya Bhowmik
Tejs Vegge
Peter Bjørn Jørgensen
Ole Winther
41
23
0
20 Jul 2022
Electronic-structure properties from atom-centered predictions of the
  electron density
Electronic-structure properties from atom-centered predictions of the electron density
Andrea Grisafi
Alan M Lewis
M. Rossi
Michele Ceriotti
19
20
0
28 Jun 2022
Accurate Machine Learned Quantum-Mechanical Force Fields for
  Biomolecular Simulations
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
43
18
0
17 May 2022
SELFIES and the future of molecular string representations
SELFIES and the future of molecular string representations
Mario Krenn
Qianxiang Ai
Senja Barthel
Nessa Carson
Angelo Frei
...
Andrew Wang
Andrew D. White
Adamo Young
Rose Yu
A. Aspuru‐Guzik
38
149
0
31 Mar 2022
Electronic excited states in deep variational Monte Carlo
Electronic excited states in deep variational Monte Carlo
M. Entwistle
Zeno Schätzle
P. A. Erdman
Jan Hermann
Frank Noé
27
45
0
17 Mar 2022
Gaussian Moments as Physically Inspired Molecular Descriptors for
  Accurate and Scalable Machine Learning Potentials
Gaussian Moments as Physically Inspired Molecular Descriptors for Accurate and Scalable Machine Learning Potentials
Viktor Zaverkin
Johannes Kastner
34
67
0
15 Sep 2021
Excited state, non-adiabatic dynamics of large photoswitchable molecules
  using a chemically transferable machine learning potential
Excited state, non-adiabatic dynamics of large photoswitchable molecules using a chemically transferable machine learning potential
Simon Axelrod
E. Shakhnovich
Rafael Gómez-Bombarelli
29
49
0
10 Aug 2021
Solving the electronic Schrödinger equation for multiple nuclear
  geometries with weight-sharing deep neural networks
Solving the electronic Schrödinger equation for multiple nuclear geometries with weight-sharing deep neural networks
Michael Scherbela
Rafael Reisenhofer
Leon Gerard
P. Marquetand
Philipp Grohs
33
47
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
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
14
1
0
15 Apr 2021
Automated and Autonomous Experiment in Electron and Scanning Probe
  Microscopy
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
40
3
0
22 Mar 2021
Machine Learning Force Fields
Machine Learning Force Fields
Oliver T. Unke
Stefan Chmiela
H. E. Sauceda
M. Gastegger
I. Poltavsky
Kristof T. Schütt
A. Tkatchenko
K. Müller
AI4CE
34
888
0
14 Oct 2020
Deep Learning for UV Absorption Spectra with SchNarc: First Steps
  Towards Transferability in Chemical Compound Space
Deep Learning for UV Absorption Spectra with SchNarc: First Steps Towards Transferability in Chemical Compound Space
Julia Westermayr
P. Marquetand
16
51
0
15 Jul 2020
Deep neural network solution of the electronic Schrödinger equation
Deep neural network solution of the electronic Schrödinger equation
J. Hermann
Zeno Schätzle
Frank Noé
152
448
0
16 Sep 2019
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