3 papers
cs.LG2026
Does Graph Compression Preserve Signal Propagation?
Kawshik Banerjee, Khaled Mohammed Saifuddin
Graph compression reduces the computational cost of graph learning, but its effect on signal propagation remains largely underexplored. Existing work evaluates compression through…
cs.LG2025
HyperGCL: Multi-Modal Graph Contrastive Learning via Learnable Hypergraph Views
Khaled Mohammed Saifuddin, Shihao Ji, Esra Akbas
Recent advancements in Graph Contrastive Learning (GCL) have demonstrated remarkable effectiveness in improving graph representations. However, relying on predefined augmentations…
cs.LG2024
Tackling Oversmoothing in GNN via Graph Sparsification: A Truss-based Approach
Tanvir Hossain, Khaled Mohammed Saifuddin, Muhammad Ifte Khairul Islam +2
Graph Neural Network (GNN) achieves great success for node-level and graph-level tasks via encoding meaningful topological structures of networks in various domains, ranging from s…