8 citations · 8 across the 6 of their papers we have counts for
5 papers · 1 filter
Causal Inference Under Network Interference
Subhankar Bhadra, Michael Schweinberger
We review the growing body of research on the challenging topic of interference in causal inference. Interference arises when the treatment assignments of connected units affect th…
A Unified Framework for Community Detection and Model Selection in Blockmodels
Subhankar Bhadra, Minh Tang, Srijan Sengupta
Blockmodels are a foundational tool for modeling community structure in networks, with the stochastic blockmodel (SBM), degree-corrected blockmodel (DCBM), and popularity-adjusted…
Scalable community detection in massive networks via predictive assignment
Subhankar Bhadra, Marianna Pensky, Srijan Sengupta
Massive network datasets are becoming increasingly common in scientific applications. Existing community detection methods encounter significant computational challenges for such m…
A regression framework for studying relationships among attributes under network interference
Cornelius Fritz, Michael Schweinberger, Subhankar Bhadra +1
To understand how the interconnected and interdependent world of the twenty-first century operates and make model-based predictions, joint probability models for networks and inter…
Detecting and Localizing Anomalous Cliques in Inhomogeneous Networks using Egonets
Subhankar Bhadra, Srijan Sengupta
Cliques, or fully connected subgraphs, are among the most important and well-studied graph motifs in network science. We consider the problem of finding a statisti- cally anomalous…