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Theoretical and Computational Chemistry

Working Paper

Machine-Learning Coupled Cluster Properties through a Density Tensor Representation

Benjamin Peyton, Connor Briggs, Ruhee D'Cunha, Johannes T. Margraf, Thomas Crawford

Version 1 posted 02 April 2020

676

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Theoretical and Computational Chemistry

Working Paper

Towards Density Functional Approximations from Coupled Cluster Correlation Energy Densities

Johannes T. Margraf, Christian Kunkel, Karsten Reuter

Version 2 posted 30 April 2019

1,183

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Theoretical and Computational Chemistry

Working Paper

Size-Extensive Molecular Machine Learning with Global Descriptors

Hyunwook Jung, Sina Stocker, Christian Kunkel, Harald Oberhofer, Byungchan Han, Karsten Reuter, Johannes T. Margraf

Version 1 posted 22 October 2019

840

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1

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Theoretical and Computational Chemistry

Working Paper

On the role of long-range electrostatics in machine-learned interatomic potentials for complex battery materials

Carsten G. Staacke, Hendrik H. Heenen, Christoph Scheurer, Gábor Csányi, Karsten Reuter, Johannes T. Margraf

Version 1 posted 26 July 2021

714

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Theoretical and Computational Chemistry

Working Paper

Learning to Use the Force: Fitting Repulsive Potentials in Density-Functional Tight-Binding with Gaussian Process Regression

Chiara Panosetti, Artur Engelmann, Lydia Nemec, Karsten Reuter, Johannes T. Margraf

Version 1 posted 02 October 2019

1,110

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Theoretical and Computational Chemistry

Working Paper

Kernel Charge Equilibration: Efficient and Accurate Prediction of Molecular Dipole Moments with a Machine-Learning Enhanced Electron Density Model

Carsten Staacke, Simon Wengert, Christian Kunkel, Gábor Csányi, Karsten Reuter, Johannes T. Margraf

Version 1 posted 25 November 2021

620

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Theoretical and Computational Chemistry

Working Paper

Reorganization energies of flexible organic molecules as a challenging target for machine learning enhanced virtual screening

Ke Chen, Christian Kunkel, Karsten Reuter, Johannes T. Margraf

Version 1 posted 24 November 2021

285

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Theoretical and Computational Chemistry

Working Paper

Regularized Second-Order Correlation Methods for Extended Systems

Elisabeth Keller, Theodoros Tsatsoulis, Karsten Reuter, Johannes T. Margraf

Version 1 posted 24 November 2021

295

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Materials Science

Working Paper

Interplay between shape and composition in bimetallic nanoparticles revealed by an efficient optimal-exchange optimization algorithm

Felix Neumann, Johannes T Margraf, Karsten Reuter, Albert Bruix

Version 1 posted 23 December 2021

205

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Theoretical and Computational Chemistry

Working Paper

How Robust are Modern Graph Neural Network Potentials in Long and Hot Molecular Dynamics Simulations?

Sina Stocker, Johannes Gasteiger, Florian Becker, Stephan Günnemann, Johannes T. Margraf

Version 1 posted 01 April 2022

1,281

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1

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Refine Search

22 results in Johannes T. Margraf in Authors: Johannes T. Margraf

Machine-Learning Coupled Cluster Properties through a Density Tensor Representation

Towards Density Functional Approximations from Coupled Cluster Correlation Energy Densities

Size-Extensive Molecular Machine Learning with Global Descriptors

On the role of long-range electrostatics in machine-learned interatomic potentials for complex battery materials

Learning to Use the Force: Fitting Repulsive Potentials in Density-Functional Tight-Binding with Gaussian Process Regression

Kernel Charge Equilibration: Efficient and Accurate Prediction of Molecular Dipole Moments with a Machine-Learning Enhanced Electron Density Model

Reorganization energies of flexible organic molecules as a challenging target for machine learning enhanced virtual screening

Regularized Second-Order Correlation Methods for Extended Systems

Interplay between shape and composition in bimetallic nanoparticles revealed by an efficient optimal-exchange optimization algorithm

How Robust are Modern Graph Neural Network Potentials in Long and Hot Molecular Dynamics Simulations?

22 results in Authors: Johannes T. Margraf