Machine learning for electronically excited states of molecules

10 July 2020

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 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 Shubhankar Agarwal Hamzah I. Khan Sandeep P. Chinchali David Fridovich-Keil 38 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 Vivin Vinod Peter Zaspel 21 0 0 15 Oct 2024
Assessing Non-Nested Configurations of Multifidelity Machine Learning for Quantum-Chemical Properties Vivin Vinod Peter Zaspel AI4CE 29 3 0 24 Jul 2024
CheMFi: A Multifidelity Dataset of Quantum Chemical Properties of Diverse Molecules Vivin Vinod Peter Zaspel 27 4 0 20 Jun 2024
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 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 Vivin Vinod Sayan Maity Peter Zaspel Ulrich Kleinekathöfer AI4CE 13 7 0 18 May 2023
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 Michael Scherbela Leon Gerard Philipp Grohs 32 8 0 17 Mar 2023
Lifelong Machine Learning Potentials Marco Eckhoff Markus Reiher 62 20 0 10 Mar 2023
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 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 M. Schreiner Arghya Bhowmik Tejs Vegge Jonas Busk Ole Winther 21 62 0 25 Jul 2022
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 Andrea Grisafi Alan M Lewis M. Rossi Michele Ceriotti 17 20 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 43 18 0 17 May 2022
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 35 149 0 31 Mar 2022
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 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 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 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 Ramin Ansari Amirata Ghorbani 14 1 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 40 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 34 888 0 14 Oct 2020
Deep Learning for UV Absorption Spectra with SchNarc: First Steps Towards Transferability in Chemical Compound Space Julia Westermayr P. Marquetand 14 51 0 15 Jul 2020
Deep neural network solution of the electronic Schrödinger equation J. Hermann Zeno Schätzle Frank Noé 149 448 0 16 Sep 2019