Accurate Shapley Value Estimation for Interpretable Deep Learning Predictive Modeling Using Energy-based Models

The article presents EmSHAP, an energy model-based approach for accurate and efficient estimation of Shapley values to interpret deep learning predictive models. EmSHAP uses a GRU network with a dynamic masking scheme to estimate the conditional probability distributions required for Shapley value calculation, overcoming the limitations of existing methods.