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A Machine-Learned "Chemical Intuition" to Overcome Spectroscopic Data Scarcity

Cailum M. K. Stienstra, Teun van Wieringen, Liam Hebert, Patrick Thomas, Kas J. Houthuijs, Giel Berden, Jos Oomens, Jonathan Martens, W. Scott Hopkins

Version 1 posted 10 December 2024

141

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Theoretical and Computational Chemistry

Working Paper

Neural Mulliken Analysis: Molecular Graphs from Density Matrices for QSPR on Raw Quantum-Chemical Data

Oleg Gromov

Version 1 posted 06 December 2024

127

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Theoretical and Computational Chemistry

Working Paper

Message Passing Neural Networks for Partial Charge Assignment to Metal-Organic Frameworks

Ali Raza, Arni Sturluson, Cory Simon, Xiaoli Fern

Version 1 posted 14 May 2020

861

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Theoretical and Computational Chemistry

Working Paper

Coloring Molecules with Explainable Artificial Intelligence for Preclinical Relevance Assessment

Jose Jimenez-Luna, Miha Skalic, Nils Weskamp, Gisbert Schneider

Version 1 posted 19 November 2020

1,199

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Theoretical and Computational Chemistry

Working Paper

Accelerating Organic Electronic Materials Design with Low-Cost, Robust Molecular Reorganization Energy Predictions

Cheng-Han Li, Daniel Tabor

Version 1 posted 30 November 2022

254

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Theoretical and Computational Chemistry

Working Paper

Materials discovery for high-temperature, clean-energy applications using graph neural network models of vacancy defects and free-energy calculations

Matthew Witman, Anuj Goyal, Tadashi Ogitsu, Anthony McDaniel, Stephan Lany

Version 2 posted 06 January 2023

2,017

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1

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Theoretical and Computational Chemistry

Working Paper

Deep Learning Metal Complex Properties with Natural Quantum Graphs

Hannes Kneiding, Ruslan Lukin, Lucas Lang, Simen Reine, Thomas Bondo Pedersen, Riccardo De Bin, David Balcells

Version 2 posted 09 November 2022

1,102

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Theoretical and Computational Chemistry

Working Paper

Enabling late-stage drug diversification by high-throughput experimentation with geometric deep learning

David F. Nippa, Kenneth Atz, Remo Hohler, Alex T. Müller, Andreas Marx, Christian Bartelmus, Georg Wuitschik, Irene Marzuoli, Vera Jost, Jens Wolfard, Martin Binder, Antonia F. Stepan, David B. Konrad, Uwe Grether, Rainer E. Martin, Gisbert Schneider

Version 2 posted 15 November 2022

2,661

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3

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Theoretical and Computational Chemistry

Working Paper

Graph transformer neural network for chemical reactivity prediction

David F. Nippa, Kenneth Atz, Alex T. Müller, Jens Wolfard, Clemens Isert, Martin Binder, Oliver Scheidegger, David B. Konrad, Uwe Grether, Rainer E. Martin, Gisbert Schneider

Version 1 posted 16 May 2023

1,287

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Physical Chemistry

Working Paper

Improving machine learning performance on small chemical reaction data with unsupervised contrastive pretraining

Mingjian Wen, Samuel M. Blau, Xiaowei Xie, Shyam Dwaraknath, Kristin A. Persson

Version 2 posted 11 January 2022

731

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66 results in graph neural networks in Keywords: graph neural networks

A Machine-Learned "Chemical Intuition" to Overcome Spectroscopic Data Scarcity

Neural Mulliken Analysis: Molecular Graphs from Density Matrices for QSPR on Raw Quantum-Chemical Data

Message Passing Neural Networks for Partial Charge Assignment to Metal-Organic Frameworks

Coloring Molecules with Explainable Artificial Intelligence for Preclinical Relevance Assessment

Accelerating Organic Electronic Materials Design with Low-Cost, Robust Molecular Reorganization Energy Predictions

Materials discovery for high-temperature, clean-energy applications using graph neural network models of vacancy defects and free-energy calculations

Deep Learning Metal Complex Properties with Natural Quantum Graphs

Enabling late-stage drug diversification by high-throughput experimentation with geometric deep learning

Graph transformer neural network for chemical reactivity prediction

Improving machine learning performance on small chemical reaction data with unsupervised contrastive pretraining

66 results in Keywords: graph neural networks