arXiv Machine Learning June 9, 2026 By Jonas Teufel, Luca Torresi, Andr\'e Eberhard, Pascal Friederich

Hyper-Dimensional Fingerprints as Molecular Representations

Read the original on arXiv Machine Learning →

arXiv:2604. 27810v2 Announce Type: replace Abstract: Computational molecular representations underpin virtual screening, property prediction, and materials discovery.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv Machine Learning

Aug 7

Physics-Based Molecular Fingerprints from Spectral Graph Theory Provide Efficient Geometry-Aware Measures of Chemical Similarity

arXiv:2608. 05336v1 Announce Type: cross Abstract: Molecular representations are essential for the evaluation of molecular similarity and the development of structure-property relationships.

By Jacob W. Toney, Ayleen Y. Farnood, Samir Darouich, Heather J. Kulik

rag

arXiv Machine Learning

Jun 19

MolGraphBench: A Benchmark of GNN Architectures for Molecular Regression Tasks

arXiv:2602. 20573v3 Announce Type: replace Abstract: Molecules are often represented as SMILES strings, which can be readily converted to hand-crafted descriptors or fingerprints (FP) for molecular property prediction.

By Rajan, Ishaan Gupta

fine-tuning benchmarks

arXiv Machine Learning

Jun 16

Spectral Analysis of Molecular Features: When Richer Features Do Not Guarantee Better Generalization

arXiv:2510. 14217v2 Announce Type: replace Abstract: The spectral properties of feature embeddings offer critical insights into model generalization and representation quality.

By Asma Jamali, Tin Sum Cheng, Rodrigo A. Vargas-Hern\'andez

llms rag benchmarks

arXiv Machine Learning

Jun 9

Advancing Ligand-based Virtual Screening and Molecular Generation with Pretrained Molecular Embedding Distance

arXiv:2604. 24474v2 Announce Type: replace Abstract: Molecular similarity plays a central role in ligand-based drug discovery, such as virtual screening, analog searching, and goal-directed molecular generation.

By Shiyun Wa, Yifei Wang, Simone Sciabola, Ye Wang

rag

arXiv Machine Learning

Aug 4

Scikit-fingerprints: Python library for scikit-learn compatible molecular fingerprints and chemoinformatics

arXiv:2608. 02027v1 Announce Type: new Abstract: We present scikit-fingerprints, a comprehensive, fully scikit-learn compatible library for molecular machine learning in Python, based on RDKit.

By Jakub Adamczyk, Adam Staniszewski

arXiv Machine Learning

Jun 9

A systematic investigation of molecular encoding methods for drug property predictions across neural network and Transformer encoder-based model

arXiv:2606. 08973v1 Announce Type: cross Abstract: Fundamental investigations into how different molecular encoding methods affect molecular property prediction remain relatively limited.

By Sheng-Ya Chen, Shan-Ju Yeh

llms safety

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Physics-Based Molecular Fingerprints from Spectral Graph Theory Provide Efficient Geometry-Aware Measures of Chemical Similarity

MolGraphBench: A Benchmark of GNN Architectures for Molecular Regression Tasks

Spectral Analysis of Molecular Features: When Richer Features Do Not Guarantee Better Generalization

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Scikit-fingerprints: Python library for scikit-learn compatible molecular fingerprints and chemoinformatics

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