3 papers
cs.LG2026
T-SNN: Temporal Simplicial Neural Network for EEG Decoding
Nikita Malik, Shubhajit Roy, Mohit Kataria +4
Decoding brain states requires models that capture both the evolution of neural activity and interactions among groups of brain regions. Existing EEG methods often treat recordings…
cs.SI2025
AH-UGC: Adaptive and Heterogeneous-Universal Graph Coarsening
Mohit Kataria, Shreyash Bhilwade, Sandeep Kumar +1
is a prominent graph reduction technique that compresses large graphs to enable efficient learning and inference. However, existing GC methods gene…
cs.LG2025
GraphFLEx: Structure Learning Framework for Large Expanding Graphs
Mohit Kataria, Nikita Malik, Sandeep Kumar +1
Graph structure learning is a core problem in graph-based machine learning, essential for uncovering latent relationships and ensuring model interpretability. However, most existin…