7 papers
A Network-Based Measure of Cosponsorship Influence on Bill Passing in the United States House of Representatives
Sarah Sotoudeh, Mason A. Porter, Sanjukta Krishnagopal
Each year, the United States Congress considers thousands of legislative proposals to select bills to present to the US President to sign into law. Naturally, the decision processe…
Sparse Contextual Coupling Reshapes Diffusion Geometry in Multilayer Hypergraphs
Hao Ding, Sanjukta Krishnagopal
Many complex systems combine dense background structure with sparse contextual information. We introduce a diffusion-based framework for analyzing how sparse condition-specific lay…
Spectral Graph Sparsification Preserves Representation Geometry in Graph Neural Networks
Sanjukta Krishnagopal
Spectral graph sparsification is a classical tool for reducing graph complexity while preserving Laplacian quadratic forms. In graph neural networks (GNNs), sparsification is often…
Topological Neural Tangent Kernel
Sanjukta Krishnagopal
Graph neural tangent kernels give a principled infinite-width theory for graph neural networks, but inherit a basic limitation of graph models: they see only pairwise structure. Ma…
Fractal dimensions of complex networks: advocating for a topological approach
Rayna Andreeva, Haydeé Contreras-Peruyero, Sanjukta Krishnagopal +3
Topological Data Analysis (TDA) uses insights from topology to create representations of data able to capture global and local geometric and topological properties. Its methods hav…
Beyond Attention: Learning Spatio-Temporal Dynamics with Emergent Interpretable Topologies
Sai Vamsi Alisetti, Vikas Kalagi, Sanjukta Krishnagopal
Spatio-temporal forecasting is critical in applications such as traffic prediction, energy demand modeling, and weather monitoring. While Graph Attention Networks (GATs) are popula…