Why is Interpretability Important in Nanotechnology?
In nanotechnology, the complexity and novelty of the materials and processes involved necessitate a deep understanding of how machine learning models derive their predictions. Interpretability helps in: - Validating models by ensuring they are based on scientifically sound principles. - Debugging models to identify and correct errors or biases. - Enhancing trust among researchers and stakeholders by providing transparency.
