4 citations · 6 across the 7 of their papers we have counts for
9 papers
EpiFlow: A framework for improving the utility of wastewater signals for disease forecasting
Aniruddha Adiga, Jingyuan Chou, Gursharn Kaur +8
Wastewater-based surveillance is an effective tool for disease monitoring and can provide early warning of outbreaks. Although wastewater viral loads (WVL) correlate with disease b…
Wastewater-based Epidemiology for COVID-19 Surveillance and Beyond: A Survey
Chen Chen, Yunfan Wang, Gursharn Kaur +10
The pandemic of COVID-19 has imposed tremendous pressure on public health systems and social economic ecosystems over the past years. To alleviate its social impact, it is importan…
Interacting Urns on Directed Networks with Node-Dependent Sampling and Reinforcement
Gursharn Kaur, Neeraja Sahasrabudhe
We consider interacting urns on a finite directed network, where both sampling and reinforcement processes depend on the nodes of the network. This extends previous research by inc…
Distributions of cherries and pitchforks for the Ford model
Gursharn Kaur, Kwok Pui Choi, Taoyang Wu
We study two fringe subtree counting statistics, the number of cherries and that of pitchforks for Ford's model, a one-parameter family of random phylogenetic tree models that…
On asymptotic joint distributions of cherries and pitchforks for random phylogenetic trees
Kwok Pui Choi, Gursharn Kaur, Taoyang Wu
Tree shape statistics provide valuable quantitative insights into evolutionary mechanisms underpinning phylogenetic trees, a commonly used graph representation of evolution systems…
Higher-order fluctuations in dense random graph models
Gursharn Kaur, Adrian Röllin
Our main results are quantitative bounds in the multivariate normal approximation of centred subgraph counts in random graphs generated by a general graphon and independent vertex…