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Explainable Molecular Property Prediction: Aligning Chemical Concepts with Predictions via Language Models
Though transformer-based language models have shown great potential in accurate molecular property prediction, they neither provide chemically meaningful explanations nor faithfully reveal the molecular structure-property relationships.
Graph Convolutional Neural Networks for Polymers Property Prediction
A fast and accurate predictive tool for polymer properties is demanding and will pave the way to iterative inverse design.
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