348 citations · 1.2k across the 81 of their papers we have counts for
30 papers · 1 filter
Joint Learning of Panel VAR models with Low Rank and Sparse Structure
Yuchen Xu, George Michailidis
Panel vector auto-regressive (VAR) models are widely used to capture the dynamics of multivariate time series across different subpopulations, where each subpopulation shares a com…
A Functional Coefficients Network Autoregressive Model
Hang Yin, Abolfazl Safikhani, George Michailidis
The paper introduces a flexible model for the analysis of multivariate nonlinear time series data. The proposed Functional Coefficients Network Autoregressive (FCNAR) model conside…
Low Tree-Rank Bayesian Vector Autoregression Model
Leo L. Duan, Zeyu Yuwen, George Michailidis +1
Vector autoregression has been widely used for modeling and analysis of multivariate time series data. In high-dimensional settings, model parameter regularization schemes inducing…
A generalized likelihood based Bayesian approach for scalable joint regression and covariance selection in high dimensions
Srijata Samanta, Kshitij Khare, George Michailidis
The paper addresses joint sparsity selection in the regression coefficient matrix and the error precision (inverse covariance) matrix for high-dimensional multivariate regression m…
A General Modeling Framework for Network Autoregressive Processes
Hang Yin, Abolfazl Safikhani, George Michailidis
The paper develops a general flexible framework for Network Autoregressive Processes (NAR), wherein the response of each node linearly depends on its past values, a prespecified li…
Multiple Change Point Detection in Reduced Rank High Dimensional Vector Autoregressive Models
Peiliang Bai, Abolfazl Safikhani, George Michailidis
We study the problem of detecting and locating change points in high-dimensional Vector Autoregressive (VAR) models, whose transition matrices exhibit low rank plus sparse structur…