5 citations · 9 across the 14 of their papers we have counts for
4 papers · 1 filter
Benchmarking Sheaf Neural Networks for Inductive Tasks
Stefano Fiorini, Edoardo Coppola, Pietro Liò
Sheaf Neural Networks (SNNs) generalize message passing by replacing scalar edge weights of standard Graph Neural Networks (GNNs) with learnable, edge-dependent restriction maps be…
Graph Transductive Sharpening: Leveraging Unlabeled Predictions in Node Classification
Brown Zaz, Mar Gonzàlez I Català, Ferran Hernandez Caralt +2
In the transductive setting, where the full graph is observed but node labels are only partially available, progress in semi-supervised node classification has largely focused on a…
Hypergraph Pattern Machine: Compositional Tokenization for Higher-Order Interactions
Kyrie Zhao, Zehong Wang, Tianyi Ma +5
Hypergraphs model higher-order relations that drive real-world decisions, from drug prescriptions to recommendations. A central structural signal in such data, beyond what pairwise…
Differentiable Retrieval-Augmented Generation for Predicting Cellular Responses to Gene Perturbation
Andrea Giuseppe Di Francesco, Andrea Rubbi, Pietro Liò +1
Predicting transcriptional responses to genetic perturbations is fundamental to functional genomics and therapeutic discovery. Recent deep learning models have shown promise in sin…