Scientific Model

Scientific modeling is evolving to integrate data-driven approaches, like machine learning (ML), with established scientific theories and domain expertise. Current research emphasizes hybrid models that combine the predictive power of ML with the explainability and generalizability offered by incorporating prior knowledge, often through knowledge graphs or guided pruning techniques. This integration aims to improve model accuracy, interpretability, and alignment with existing scientific understanding, leading to more reliable predictions and insights across diverse fields, such as language processing, gene regulatory networks, and chemical engineering.