Knockoffs are a popular statistical tool for conditional variable selection in high dimension.

A common approach to create more expressive GNNs is to change the message passing function of MPNNs. If a GNN is more expressive than MPNNs by adapting the message passing function, we call this non-standard message passing . Examples of this are message passing variants that operate on subgraphs [Frasca et al., 2022, Bevilacqua

Data poisoning considers cases when an adversary manipulates the behavior of machine learning algorithms through malicious training data.

In this work, we propose a peer-to-peer (P2P) learning scheme that is secure against malicious servers and robust to malicious clients.