Sharif Digital Repository

The exploration of chemical molecule properties and their underlying reasons, along with the interpretability of machine learning models and artificial intelligence, constitutes a pivotal concern in their respective domains. Numerous research endeavors have been undertaken to address these challenges. Uncovering the existence and rationales behind the chemical properties in molecules enhances our comprehension of diverse substances and instills greater confidence. Among various algorithms and computational approaches, graph neural networks emerge as a significant solution for modeling and computation in molecular research. Moreover, these networks offer modern interpretability methods. This...