Marco Gatti

Sum-of-Parts: Self-Attributing Neural Networks with End-to-End Learning of Feature Groups

Self-attributing neural networks (SANNs) present a potential path towards interpretable models for high-dimensional problems, but often face significant trade-offs in performance. In this work, we formally prove a lower bound on errors of per-feature SANNs, whereas group-based SANNs can achieve zero…