Implementation of an activation-based visual attribution method for irregular graphs, which works integrated with graph convolutional neural networks (GCNs). The method has been validated via a sex classification task using functional brain connectivity networks and data from the UK Biobank and is presented in our paper, Arslan et al., Graph Saliency Maps through Spectral Convolutional Networks: Application to Sex Classification with Brain Connectivity (arxiv). See the GitHub page for more details.