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stat.ME2026
Universal Inference for model selection on networks
Eric Yanchenko, Jonathan P. Williams, Ryan Martin
Model selection and hypothesis testing are important tasks on networks. A key challenge lies in the inherent dependence in network data, as well as the fact that typically only a s…
stat.ME2026
Hypothesis testing for community structure in temporal networks using e-values
Eric Yanchenko, Jonathan P. Williams, Ryan Martin
Community structure in networks naturally arises in various applications. But while the topic has received significant attention for static networks, the literature on community st…
stat.ME2025
Statistical inference for core-periphery structures
Eric Yanchenko, Srijan Sengupta, Diganta Mukherjee
Core-periphery (CP) structure is an important meso-scale network property where nodes group into a small, densely interconnected {core} and a sparse {periphery} whose members prima…