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Theoretical and Computational Chemistry

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Explaining compound activity predictions with a substructure-aware loss for graph neural networks

Kenza Amara, Raquel Rodriguez-Perez, José Jiménez Luna

Version 4 posted 05 April 2023

937

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Polymer Science

Working Paper

Machine learning to explain printability induced by rheology additives

Ali Nadernezhad, Jürgen Groll

Version 1 posted 13 December 2021

416

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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

1,133

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Theoretical and Computational Chemistry

Working Paper

ChemInformatics Model Explorer (CIME): Exploratory analysis of chemical model explanations

Christina Humer, Henry Heberle, Floriane Montanari, Thomas Wolf, Florian Huber, Ryan Henderson, Julian Heinrich, Marc Streit

Version 1 posted 01 December 2021

493

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Theoretical and Computational Chemistry

Working Paper

Explainable Uncertainty Quantifications for Deep Learning-Based Molecular Property Prediction

Chu-I Yang, Yi-Pei Li

Version 1 posted 12 September 2022

495

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Theoretical and Computational Chemistry

Working Paper

Interpretable Molecular Property Predictions Using Marginalized Graph Kernels

Yan Xiang, Yu-Hang Tang, Guang Lin, Daniel Reker

Version 1 posted 20 February 2023

394

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Theoretical and Computational Chemistry

Working Paper

Benchmarking molecular feature attribution methods with activity cliffs

José Jiménez Luna, Miha Skalic, Nils Weskamp

Version 1 posted 17 September 2021

1,276

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Theoretical and Computational Chemistry

Working Paper

CIME4R: Exploring iterative, AI-guided chemical reaction optimization campaigns in their parameter space

Christina Humer, Rachel Nicholls, Henry Heberle, Moritz Heckmann, Michael Pühringer, Thomas Wolf, Maximilian Lübbesmeyer, Julian Heinrich, Julius Hillenbrand, Giulio Volpin, Marc Streit

Version 1 posted 22 December 2023

196

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Biological and Medicinal Chemistry

Working Paper

Interpreting Graph Neural Networks with Myerson Values for Cheminformatics Approaches

Samuel Homberg, Menke Janosch, Garrett M. Morris, Oliver Koch

Version 1 posted 08 May 2023

402

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Polymer Science

Working Paper

Polymer Reaction Engineering meets Explainable Machine Learning

Jelena Fiosina, Philipp Sievers, Marco Drache, Sabine Beuermann

Version 1 posted 06 April 2023

323

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13 results in explainable AI in Keywords: explainable AI

Explaining compound activity predictions with a substructure-aware loss for graph neural networks

Machine learning to explain printability induced by rheology additives

Coloring Molecules with Explainable Artificial Intelligence for Preclinical Relevance Assessment

ChemInformatics Model Explorer (CIME): Exploratory analysis of chemical model explanations

Explainable Uncertainty Quantifications for Deep Learning-Based Molecular Property Prediction

Interpretable Molecular Property Predictions Using Marginalized Graph Kernels

Benchmarking molecular feature attribution methods with activity cliffs

CIME4R: Exploring iterative, AI-guided chemical reaction optimization campaigns in their parameter space

Interpreting Graph Neural Networks with Myerson Values for Cheminformatics Approaches

Polymer Reaction Engineering meets Explainable Machine Learning

13 results in Keywords: explainable AI