3 citations · 3 across the 3 of their papers we have counts for
3 papers
Inductive Correlation Clustering with Graph Neural Networks
Francesco Paolo Nerini, Francesco Bonchi, Arijit Khan +1
Correlation Clustering (CC) is a natural formulation of clustering in combinatorial optimization, which uses a graph representation of the input and does not require a pre-specifie…
HyDRA: Lossless Hypergraph Summarization via Co-Clustering
Giulia Preti, Aris Anagnostopoulos, Francesco Bonchi
Hypergraphs are a powerful representation for higher-order interactions but their scale and complexity pose significant data management and analysis challenges. While summarization…
Finding Counterfactual Evidences for Node Classification
Dazhuo Qiu, Jinwen Chen, Arijit Khan +2
Counterfactual learning is emerging as an important paradigm, rooted in causality, which promises to alleviate common issues of graph neural networks (GNNs), such as fairness and i…