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Chemistry

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DAR-GNN: Dynamic Anchor Relational Graph Neural Network for Efficient ADMET Property Prediction with Left-Censored Labels

Haowen Shi, Yichen Zong

Version 1 posted 28 December 2025

7

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Chemistry

Working Paper

Molecular Graph Transformer: Stepping Beyond ALIGNN Into Long-Range Interactions

Marco Anselmi, Greg Slabaugh, Rachel Crespo-Otero, Devis Di Tommaso

Version 1 posted 22 January 2024

819

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Chemistry

Working Paper

Experiments with data-augmented modeling of ADME and potency endpoints in the ASAP-Polaris-OpenADMET Antiviral Challenge

Mounika Srilakshmi, Ida Titus, Ashok Palaniappan

Version 1 posted 10 September 2025

388

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Computer Science

Working Paper

Enhancing Transformer with GNN Structural Knowledge via Distillation: A Novel Approach

Zhihua Duan, Jialin Wang

Version 1 posted 28 February 2025

22

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Chemistry

Working Paper

KGG: Knowledge-Guided Graph Self-Supervised Learning to Enhance Molecular Property Predictions

Van-Thinh To, Phuoc-Chung Van-Nguyen, Gia-Bao Truong, Tuyet-Minh Phan, Tieu-Long Phan, Rolf Fagerberg, Peter Stadler, Tuyen Truong

Version 1 posted 25 April 2025

534

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Chemistry

Working Paper

Navigating Materials Space with ML-Generated Electronic Fingerprints

Ihor Neporozhnii, Zhibo Wang, Rochan Bajpai, Camilo Gómez, Nirvik Chakraborty, Tony Dong, Isaac Tamblyn, Oleksandr Voznyy

Version 2 posted 12 June 2024

990

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1

Citations

Chemistry

Working Paper

Interpreting Graph Neural Networks with Myerson Values for Cheminformatics Approaches

Samuel K. R. Homberg, Malte L. Modlich, Janosch Menke, Garrett M. Morris, Benjamin Risse, Oliver Koch

Version 2 posted 09 July 2024

1,608

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1

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Chemistry

Working Paper

Graph neural networks predict energetic and mechanical properties for models of solid solution metal alloy phases

Massimiliano Lupo Pasini, GS Jung, Stephan Irle

Version 2 posted 25 October 2022

636

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Chemistry

Working Paper

InFrag: Using Attribution-based Explainability to Guide Deep Molecular Optimization

Pierre Wüthrich, Jun Jin Choong, Shinya Yuki

Version 1 posted 13 September 2021

601

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1

Citations

Chemistry

Working Paper

graphpancake: A Python package for representing organic molecules as molecular graphs utilizing electronic structure theory

Karl Scheidt, Sneha Sil, Mark Maskeri

Version 1 posted 15 December 2025

92

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Refine Search

10 results in Graph Neural Networks in Keywords: Graph Neural Networks

DAR-GNN: Dynamic Anchor Relational Graph Neural Network for Efficient ADMET Property Prediction with Left-Censored Labels

Molecular Graph Transformer: Stepping Beyond ALIGNN Into Long-Range Interactions

Experiments with data-augmented modeling of ADME and potency endpoints in the ASAP-Polaris-OpenADMET Antiviral Challenge

Enhancing Transformer with GNN Structural Knowledge via Distillation: A Novel Approach

KGG: Knowledge-Guided Graph Self-Supervised Learning to Enhance Molecular Property Predictions

Navigating Materials Space with ML-Generated Electronic Fingerprints

Interpreting Graph Neural Networks with Myerson Values for Cheminformatics Approaches

Graph neural networks predict energetic and mechanical properties for models of solid solution metal alloy phases

InFrag: Using Attribution-based Explainability to Guide Deep Molecular Optimization

graphpancake: A Python package for representing organic molecules as molecular graphs utilizing electronic structure theory

10 results in Keywords: Graph Neural Networks