24 citations · 60 across the 14 of their papers we have counts for
15 papers
Non-asymptotic inference for multivariate change point detection
Ian Barnett
Traditional methods for inference in change point detection often rely on a large number of observed data points and can be inaccurate in non-asymptotic settings. With the rise of…
The impact of the COVID-19 pandemic on daily rhythms
Nguyen Luong, Ian Barnett, Talayeh Aledavood
The COVID-19 pandemic has significantly impacted daily activity rhythms and life routines. Understanding the dynamics of these impacts on different groups of people is essential fo…
A Generalized Estimating Equation Approach to Network Regression
Riddhi Pratim Ghosh, Jukka-Pekka Onnela, Ian Barnett
Regression models applied to network data where node attributes are the dependent variables poses a methodological challenge. As has been well studied, naive regression neither pro…
Selecting a significance level in sequential testing procedures for community detection
Riddhi Pratim Ghosh, Ian Barnett
While there have been numerous sequential algorithms developed to estimate community structure in networks, there is little available guidance and study of what significance level…
Confidence Intervals for the Number of Components in Factor Analysis and Principal Components Analysis via Subsampling
Chetkar Jha, Ian Barnett
Factor analysis (FA) and principal component analysis (PCA) are popular statistical methods for summarizing and explaining the variability in multivariate datasets. By default, FA…
Sparse Neural Additive Model: Interpretable Deep Learning with Feature Selection via Group Sparsity
Shiyun Xu, Zhiqi Bu, Pratik Chaudhari +1
Interpretable machine learning has demonstrated impressive performance while preserving explainability. In particular, neural additive models (NAM) offer the interpretability to th…
Multiple Hypothesis Testing To Estimate The Number of Communities in Sparse Stochastic Block Models
Chetkar Jha, Mingyao Li, Ian Barnett
Network-based clustering methods frequently require the number of communities to be specified \emph{a priori}. Moreover, most of the existing methods for estimating the number of c…
Combining Mixed Effects Hidden Markov Models with Latent Alternating Recurrent Event Processes to Model Diurnal Active-Rest Cycles
Benny Ren, Ian Barnett
Data collected from wearable devices and smartphones can shed light on an individual's pattern of behavioral and circadian routine. Phone use can be modeled as alternating event pr…
Autoregressive Mixture Models for Serial Correlation Clustering of Time Series Data
Benny Ren, Ian Barnett
Clustering time series into similar groups can improve models by combining information across like time series. While there is a well developed body of literature for clustering of…
The Asymptotic Distribution of Modularity in Weighted Signed Networks
Rong Ma, Ian Barnett
Modularity is a popular metric for quantifying the degree of community structure within a network. The distribution of the largest eigenvalue of a network's edge weight or adjacenc…
Novel Non-Negative Variance Estimator for (Modified) Within-Cluster Resampling
Daniel Xu, Pamela Shaw, Ian Barnett
This article proposes a novel variance estimator for within-cluster resampling (WCR) and modified within-cluster resampling (MWCR) - two existing methods for analyzing longitudinal…
Feature-Based Classification of Networks
Ian Barnett, Nishant Malik, Marieke L. Kuijjer +2
Network representations of systems from various scientific and societal domains are neither completely random nor fully regular, but instead appear to contain recurring structural…
Inferring Mobility Measures from GPS Traces with Missing Data
Ian Barnett, Jukka-Pekka Onnela
With increasing availability of smartphones with GPS capabilities, large-scale studies relating individual-level mobility patterns to a wide variety of patient-centered outcomes, f…
Social and Spatial Clustering of People at Humanity's Largest Gathering
Ian Barnett, Tarun Khanna, Jukka-Pekka Onnela
Macroscopic behavior of scientific and societal systems results from the aggregation of microscopic behaviors of their constituent elements, but connecting the macroscopic with the…
Change Point Detection in Correlation Networks
Ian Barnett, Jukka-Pekka Onnela
Many systems of interacting elements can be conceptualized as networks, where network nodes represent the elements and network ties represent interactions between the elements. In…