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Found 3 papers, 1 papers with code
DeepRicci: Self-supervised Graph Structure-Feature Co-Refinement for Alleviating Over-squashing
Graph Neural Networks (GNNs) have shown great power for learning and mining on graphs, and Graph Structure Learning (GSL) plays an important role in boosting GNNs with a refined graph.
Motif-aware Riemannian Graph Neural Network with Generative-Contrastive Learning
In light of the issues above, we propose the problem of \emph{Motif-aware Riemannian Graph Representation Learning}, seeking a numerically stable encoder to capture motif regularity in a diverse-curvature manifold without labels.
Bayesian Robust Tensor Ring Model for Incomplete Multiway Data
Robust tensor completion (RTC) aims to recover a low-rank tensor from its incomplete observation with outlier corruption.
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