Machine Learning Molecular Dynamics for the Simulation of Infrared Spectra

16 May 2017

Papers citing "Machine Learning Molecular Dynamics for the Simulation of Infrared Spectra"

50 / 56 papers shown

Title
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Kehan Guo Yili Shen Gisela Abigail Gonzalez-Montiel Yue Huang Yujun Zhou ... Zhichun Guo Prayel Das Nitesh Chawla Olaf Wiest Wei Wei 227 2 0 14 Feb 2025
Deep Neural Network for Phonon-Assisted Optical Spectra in Semiconductors Qiangqiang Gu S. K. Pandey Zhanghao Zhouyin 132 0 0 02 Feb 2025
Advancing Machine Learning in Industry 4.0: Benchmark Framework for Rare-event Prediction in Chemical Processes Vikram Sudarshan Warren D. Seider 98 2 0 31 Aug 2024
Physics-informed active learning for accelerating quantum chemical simulations Yi-Fan Hou Lina Zhang Quanhao Zhang Fuchun Ge Pavlo O. Dral AI4CE 76 5 0 18 Apr 2024
LTAU-FF: Loss Trajectory Analysis for Uncertainty in Atomistic Force Fields Joshua A. Vita Amit Samanta Fei Zhou Vincenzo Lordi 65 3 0 01 Feb 2024
Uncertainty-biased molecular dynamics for learning uniformly accurate interatomic potentials Viktor Zaverkin David Holzmüller Henrik Christiansen Federico Errica Francesco Alesiani Makoto Takamoto Mathias Niepert Johannes Kastner AI4CE 84 19 0 03 Dec 2023
Thermally Averaged Magnetic Anisotropy Tensors via Machine Learning Based on Gaussian Moments Viktor Zaverkin Julia Netz Fabian Zills Andreas Köhn Johannes Kastner AI4CE 49 18 0 03 Dec 2023
Predicting Properties of Periodic Systems from Cluster Data: A Case Study of Liquid Water Viktor Zaverkin David Holzmüller Robin Schuldt Johannes Kastner 68 18 0 03 Dec 2023
From Peptides to Nanostructures: A Euclidean Transformer for Fast and Stable Machine Learned Force Fields J. Frank Oliver T. Unke Klaus-Robert Muller Stefan Chmiela 69 3 0 21 Sep 2023
Scaling Spherical CNNs Carlos Esteves Jean-Jacques E. Slotine A. Makadia GNN LRM 85 14 0 08 Jun 2023
SchNetPack 2.0: A neural network toolbox for atomistic machine learning Kristof T. Schütt Stefaan S. P. Hessmann Niklas W. A. Gebauer Jonas Lederer M. Gastegger 83 65 0 11 Dec 2022
Transfer learning for chemically accurate interatomic neural network potentials Viktor Zaverkin David Holzmüller Luca Bonfirraro Johannes Kastner 101 25 0 07 Dec 2022
Edge Direction-invariant Graph Neural Networks for Molecular Dipole Moments Prediction Yang Jeong Park GNN 30 1 0 26 Jun 2022
So3krates: Equivariant attention for interactions on arbitrary length-scales in molecular systems J. Frank Oliver T. Unke Klaus-Robert Muller 89 44 0 28 May 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 70 18 0 17 May 2022
Accurate Molecular-Orbital-Based Machine Learning Energies via Unsupervised Clustering of Chemical Space Lixue Cheng Jiace Sun Thomas F. Miller 48 13 0 21 Apr 2022
Fast and Sample-Efficient Interatomic Neural Network Potentials for Molecules and Materials Based on Gaussian Moments Viktor Zaverkin David Holzmüller Ingo Steinwart Johannes Kastner 72 21 0 20 Sep 2021
Inverse design of 3d molecular structures with conditional generative neural networks Niklas W. A. Gebauer M. Gastegger Stefaan S. P. Hessmann Klaus-Robert Muller Kristof T. Schütt AI4CE 259 180 0 10 Sep 2021
Training Algorithm Matters for the Performance of Neural Network Potential: A Case Study of Adam and the Kalman Filter Optimizers Yunqi Shao Florian M. Dietrich Carl Nettelblad Chao Zhang 37 12 0 08 Sep 2021
Detect the Interactions that Matter in Matter: Geometric Attention for Many-Body Systems Thorben Frank Stefan Chmiela 60 3 0 04 Jun 2021
SpookyNet: Learning Force Fields with Electronic Degrees of Freedom and Nonlocal Effects Oliver T. Unke Stefan Chmiela M. Gastegger Kristof T. Schütt H. E. Sauceda K. Müller 234 255 0 01 May 2021
Equivariant message passing for the prediction of tensorial properties and molecular spectra Kristof T. Schütt Oliver T. Unke M. Gastegger 118 545 0 05 Feb 2021
Machine learning of solvent effects on molecular spectra and reactions M. Gastegger Kristof T. Schütt Klaus-Robert Muller AI4CE 71 62 0 28 Oct 2020
Machine Learning Force Fields Oliver T. Unke Stefan Chmiela H. E. Sauceda M. Gastegger I. Poltavsky Kristof T. Schütt A. Tkatchenko K. Müller AI4CE 143 940 0 14 Oct 2020
Machine Learning a Molecular Hamiltonian for Predicting Electron Dynamics Harish S. Bhat Karnamohit Ranka Christine M Isborn 50 12 0 19 Jul 2020
Deep Learning for UV Absorption Spectra with SchNarc: First Steps Towards Transferability in Chemical Compound Space Julia Westermayr P. Marquetand 88 53 0 15 Jul 2020
Machine learning for electronically excited states of molecules Julia Westermayr P. Marquetand 71 266 0 10 Jul 2020
Committee neural network potentials control generalization errors and enable active learning Christoph Schran K. Brezina O. Marsalek 53 131 0 02 Jun 2020
Machine learning and excited-state molecular dynamics Julia Westermayr P. Marquetand AI4CE 61 56 0 28 May 2020
Autonomous discovery in the chemical sciences part I: Progress Connor W. Coley Natalie S. Eyke K. Jensen 71 218 0 30 Mar 2020
Predicting molecular dipole moments by combining atomic partial charges and atomic dipoles M. Veit D. Wilkins Yang Yang R. DiStasio Michele Ceriotti 68 94 0 27 Mar 2020
Automated discovery of a robust interatomic potential for aluminum Justin S. Smith B. Nebgen N. Mathew Jie Chen Nicholas Lubbers ... S. Tretiak H. Nam T. Germann S. Fensin K. Barros 46 83 0 10 Mar 2020
Combining SchNet and SHARC: The SchNarc machine learning approach for excited-state dynamics Julia Westermayr M. Gastegger P. Marquetand AI4CE 67 131 0 17 Feb 2020
Big-Data Science in Porous Materials: Materials Genomics and Machine Learning Kevin Maik Jablonka D. Ongari S. M. Moosavi B. Smit AI4CE 85 365 0 18 Jan 2020
On-the-fly Prediction of Protein Hydration Densities and Free Energies using Deep Learning A. Ghanbarpour Amr H. Mahmoud M. Lill 3DH AI4CE 25 4 0 07 Jan 2020
Neural networks and kernel ridge regression for excited states dynamics of CH $_2$ NH $_2^+$ : From single-state to multi-state representations and multi-property machine learning models Julia Westermayr Felix A Faber Anders S. Christensen O. von Lilienfeld P. Marquetand 39 40 0 18 Dec 2019
Machine learning for molecular simulation Frank Noé A. Tkatchenko K. Müller C. Clementi AI4CE 90 668 0 07 Nov 2019
ProDyn0: Inferring calponin homology domain stretching behavior using graph neural networks Ali Madani Cyna R Shirazinejad Jia Rui Ong Hengameh Shams M. Mofrad 42 0 0 22 Oct 2019
Learning Everywhere: A Taxonomy for the Integration of Machine Learning and Simulations Geoffrey C. Fox S. Jha AI4CE 72 13 0 29 Sep 2019
Recurrent Neural Network-based Model for Accelerated Trajectory Analysis in AIMD Simulations M. Eslamibidgoli Mehrdad Mokhtari M. Eikerling 61 13 0 23 Sep 2019
Regression-clustering for Improved Accuracy and Training Cost with Molecular-Orbital-Based Machine Learning Lixue Cheng Nikola B. Kovachki Matthew Welborn Thomas F. Miller 82 45 0 04 Sep 2019
Unifying machine learning and quantum chemistry -- a deep neural network for molecular wavefunctions Kristof T. Schütt M. Gastegger A. Tkatchenko K. Müller R. Maurer AI4CE 98 390 0 24 Jun 2019
Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules Niklas W. A. Gebauer M. Gastegger Kristof T. Schütt 164 211 0 02 Jun 2019
Fast Neural Network Approach for Direct Covariant Forces Prediction in Complex Multi-Element Extended Systems J. Mailoa M. Kornbluth Simon L. Batzner G. Samsonidze Stephen T Lam Chris Ablitt N. Molinari Boris Kozinsky 79 54 0 07 May 2019
Learning Everywhere: Pervasive Machine Learning for Effective High-Performance Computation Geoffrey C. Fox J. Glazier J. Kadupitiya V. Jadhao Minje Kim ... Madhav Marathe Abhijin Adiga Jiangzhuo Chen O. Beckstein S. Jha 59 53 0 27 Feb 2019
Molecular Dynamics with Neural-Network Potentials M. Gastegger P. Marquetand AI4CE 31 22 0 18 Dec 2018
A Preliminary Study of Neural Network-based Approximation for HPC Applications Wenqian Dong Luanzheng Guo Dong Li 16 0 0 18 Dec 2018
Learning representations of molecules and materials with atomistic neural networks Kristof T. Schütt A. Tkatchenko K. Müller NAI 45 13 0 11 Dec 2018
Machine learning enables long time scale molecular photodynamics simulations Julia Westermayr M. Gastegger M. Menger Sebastian Mai L. González Marquetand AI4CE 49 74 0 22 Nov 2018
Compressing physical properties of atomic species for improving predictive chemistry John E. Herr Kevin J Koh Kun Yao John A. Parkhill AI4CE 55 20 0 31 Oct 2018