Minimal Explanations for Neural Network Predictions. (arXiv:2205.09901v1 [cs.LG])

Explaining neural network predictions is known to be a challenging problem.
In this paper, we propose a novel approach which can be effectively exploited,
either in isolation or in combination with other methods, to enhance the
interpretability of neural model predictions. For a given input to a trained
neural model, our aim is to compute a smallest set of input features so that
the model prediction changes when these features are disregarded by setting
them to an uninformative baseline value. …

arxiv network neural network predictions