Author

Srajan Agarwal

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#machine learning Preprint Oct 2026

HyperFuse: Fast Self-Supervised Node Embeddings for Attributed Hypergraphs

Self-supervised hypergraph representation learning can produce informative node embeddings, but existing methods often require deep encoders trained for hundreds of epochs, making embedding generation costly even for hypergraphs with a few thousand nodes. This limits applications requiring embeddings for many or evolvi...

P. Megha, Harshit Kumar, Srajan Agarwal et al. · 0 citations

#machine learning Preprint Sep 2026

Extremely Fast and Compact Binary Graph Representations via Randomized Operator Sketching

Graph neural networks typically rely on dense, floating-point node representations, which can impose substantial memory and computational costs. Binary graph hashing offers an alternative by encoding node information as compact bit strings. However, existing approaches either sacrifice global topological information fo...

Srajan Agarwal, P. Megha, Bikas C. Das et al. · 0 citations