activity
20232025
most citedAttribute network models, stochastic approximation, and network sampling and ranking algorithms

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

math.PR2025

Non-equilibrium coagulation processes and subcritical percolation on evolving networks

Sayan Banerjee, Shankar Bhamidi, Remco van der Hofstad +1

We investigate percolation on growing networks where the evolution of connected components resembles a non-equilibrium version of the multiplicative coalescent. The supercritical $…

math.PR2024

Network evolution with mesoscopic delay

Sayan Banerjee, Shankar Bhamidi, Partha Dey +1

Owing to the influence of real-world networks both in science and society, numerous mathematical models have been developed to understand the structure and evolution of these syste…

math.PR2024

Network evolution with Macroscopic Delays: asymptotics and condensation

Sayan Banerjee, Shankar Bhamidi, Partha Dey +1

Preferential attachment models typically assume that each arriving vertex observes the current network before choosing its connection. Motivated by distributed systems and social n…

math.PR2024

Local weak convergence and its applications

Sayan Banerjee, Shankar Bhamidi, Jianan Shen +1

Motivated in part by understanding average case analysis of fundamental algorithms in computer science, and in part by the wide array of network data available over the last decade…

math.PR2023★ 1 cited

Attribute network models, stochastic approximation, and network sampling and ranking algorithms

Nelson Antunes, Sayan Banerjee, Shankar Bhamidi +1

We analyze dynamic random network models where younger vertices connect to older ones with probabilities proportional to their degrees as well as a propensity kernel governed by th…