Mixing Time of Exponential Random Graphs. - Shankar Bhamidi; Guy Bresler; Allan Sly (FOCS, 2008)

Edge flows in the complete random-lengths network. - David J. Aldous; Shankar Bhamidi (Random Struct. Algorithms, 2010)

Network delay inference from additive metrics. - Shankar Bhamidi; Ram Rajagopal; Sébastien Roch (Random Struct. Algorithms, 2010)

First Passage Percolation on the Erdős-Rényi Random Graph. - Shankar Bhamidi; Remco van der Hofstad; Gerard Hooghiemstra (Comb. Probab. Comput., 2011)

A Testing Based Extraction Algorithm for Identifying Significant Communities in Networks. - James D. Wilson; Simi Wang; Peter J. Mucha; Shankar Bhamidi; Andrew B. Nobel (CoRR, 2013)

Bounded-Size Rules: The Barely Subcritical Regime. - Shankar Bhamidi; Amarjit Budhiraja; Xuan Wang (Comb. Probab. Comput., 2014)

The front of the epidemic spread and first passage percolation. - Shankar Bhamidi; Remco van der Hofstad; Júlia Komjáthy (J. Appl. Probab., 2014)

Exceptional rotations of random graphs: a VC theory. - Louigi Addario-Berry; Shankar Bhamidi; Sébastien Bubeck; Luc Devroye; Gábor Lugosi; Roberto Imbuzeiro Oliveira (J. Mach. Learn. Res., 2015)

Aggregation models with limited choice and the multiplicative coalescent. - Shankar Bhamidi; Amarjit Budhiraja; Xuan Wang (Random Struct. Algorithms, 2015)

The Continuous Configuration Model: A Null for Community Detection on Weighted Networks. - John Palowitch; Shankar Bhamidi; Andrew B. Nobel (CoRR, 2016)

Diameter of the Stochastic Mean-Field Model of Distance. - Shankar Bhamidi; Remco van der Hofstad (Comb. Probab. Comput., 2017)

Significance-based community detection in weighted networks. - John Palowitch; Shankar Bhamidi; Andrew B. Nobel (J. Mach. Learn. Res., 2017)

Community Extraction in Multilayer Networks with Heterogeneous Community Structure. - James D. Wilson; John Palowitch; Shankar Bhamidi; Andrew B. Nobel (J. Mach. Learn. Res., 2017)

Stochastic weighted graphs: Flexible model specification and simulation. - James D. Wilson; Matthew J. Denny; Shankar Bhamidi; Skyler J. Cranmer; Bruce A. Desmarais (Soc. Networks, 2017)

Sampling-based Estimation of In-degree Distribution with Applications to Directed Complex Networks. - Nelson Antunes; Shankar Bhamidi; Tianjian Guo; Vladas Pipiras; Bang Wang 003 (CoRR, 2018)

Demarcating Geographic Regions using Community Detection in Commuting Networks. - Mark He; Joseph Glasser; Nathaniel Pritchard; Shankar Bhamidi; Nikhil Kaza (CoRR, 2019)

Intertemporal Community Detection in Bikeshare Networks. - Mark He; Joseph Glasser; Shankar Bhamidi; Nikhil Kaza (CoRR, 2019)

Geometry of the vacant set left by random walk on random graphs, Wright's constants, and critical random graphs with prescribed degrees. - Shankar Bhamidi; Sanchayan Sen (Random Struct. Algorithms, 2020)

Community detection using low-dimensional network embedding algorithms. - Aman Barot; Shankar Bhamidi; Souvik Dhara (CoRR, 2021)

Sampling Based Estimation of In-Degree Distribution for Directed Complex Networks. - Nelson Antunes; Shankar Bhamidi; Tianjian Guo; Vladas Pipiras; Bang Wang 003 (J. Comput. Graph. Stat., 2021)

A probabilistic approach to the leader problem in random graphs. - Louigi Addario-Berry; Shankar Bhamidi; Sanchayan Sen (Random Struct. Algorithms, 2021)

Learning Attribute Distributions Through Random Walks. - Nelson Antunes; Shankar Bhamidi; Vladas Pipiras (COMPLEX NETWORKS (2), 2022)

Community modulated recursive trees and population dependent branching processes. - Shankar Bhamidi; Ruituo Fan; Nicolas Fraiman; Andrew B. Nobel (Random Struct. Algorithms, 2022)

Minority Representation and Relative Ranking in Sampling Attributed Networks. - Nelson Antunes; Sayan Banerjee; Shankar Bhamidi; Vladas Pipiras (COMPLEX NETWORKS (1), 2023)

Consistency of Lloyd's Algorithm Under Perturbations. - Dhruv Patel; Hui Shen; Shankar Bhamidi; Yufeng Liu; Vladas Pipiras (CoRR, 2023)

Improved baselines for causal structure learning on interventional data. - Robin Richter; Shankar Bhamidi; Sach Mukherjee (Stat. Comput., 2023)

Learning attribute and homophily measures through random walks. - Nelson Antunes; Sayan Banerjee; Shankar Bhamidi; Vladas Pipiras (Appl. Netw. Sci., 2023)

Statistical Significance of Clustering with Multidimensional Scaling. - Hui Shen; Shankar Bhamidi; Yufeng Liu (J. Comput. Graph. Stat., 2024)

Representation, ranking and bias of minorities in sampling attributed networks. - Nelson Antunes; Sayan Banerjee; Shankar Bhamidi; Vladas Pipiras (Soc. Netw. Anal. Min., 2024)