23 citations · 48 across the 6 of their papers we have counts for
6 papers
Latency correction in sparse neuronal spike trains with overlapping global events
Arturo Mariani, Federico Senocrate, Jason Mikiel-Hunter +5
Background: In Kreuz et al., J Neurosci Methods 381, 109703 (2022) two methods were proposed that perform latency correction, i.e., optimize the spike time alignment of sparse neur…
Dynamic clustering for heterophilic stochastic block models with time-varying node memberships
Kevin Z Lin, Jing Lei
We consider a time-ordered sequence of networks stemming from stochastic block models where nodes gradually change their memberships over time, and no network at any single time po…
Statistically and Computationally Efficient Change Point Localization in Regression Settings
Daren Wang, Zifeng Zhao, Kevin Lin +1
Detecting when the underlying distribution changes for the observed time series is a fundamental problem arising in a broad spectrum of applications. In this paper, we study multip…
Post-Selection Inference for Changepoint Detection Algorithms with Application to Copy Number Variation Data
Sangwon Hyun, Kevin Lin, Max G'Sell +1
Changepoint detection methods are used in many areas of science and engineering, e.g., in the analysis of copy number variation data, to detect abnormalities in copy numbers along…
Can the Stochastic Wave Equation with Strong Drift Hit Zero?
Kevin Lin, Carl Mueller
We study the stochastic wave equation with multiplicative noise and singular drift: \[ \partial_tu(t,x)=Δu(t,x)+u^{-α}(t,x)+g(u(t,x))\dot{W}(t,x) \] where lies in the circle $\…
Approximate Recovery in Changepoint Problems, from Estimation Error Rates
Kevin Lin, James Sharpnack, Alessandro Rinaldo +1
In the 1-dimensional multiple changepoint detection problem, we prove that any procedure with a fast enough error rate, in terms of its estimation of the underlying piecew…