Cross-Modal Learning for Chemistry Property Prediction: Large Language Models Meet Graph Machine Learning

In the field of chemistry, the objective is to create novel molecules with desired properties, facilitating accurate property predictions for applications such as material design and drug screening. However, existing graph deep learning methods face limitations that curb their expressive power. To a...

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Veröffentlicht in:	arXiv.org 2024-08
Hauptverfasser:	Sakhinana Sagar Srinivas, Runkana, Venkataramana
Format:	Artikel
Sprache:	eng
Schlagworte:	Deep learning Effectiveness Graph neural networks Harnesses Large language models Machine learning Molecular properties Predictions Structured data
Online-Zugang:	Volltext
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