284 citations · 335 across the 7 of their papers we have counts for
5 papers · 1 filter
An Efficient ADMM Algorithm for Structural Break Detection in Multivariate Time Series
Alex Tank, Emily B. Fox, Ali Shojaie
We present an efficient alternating direction method of multipliers (ADMM) algorithm for segmenting a multivariate non-stationary time series with structural breaks into stationary…
An Interpretable and Sparse Neural Network Model for Nonlinear Granger Causality Discovery
Alex Tank, Ian Cover, Nicholas J. Foti +2
While most classical approaches to Granger causality detection repose upon linear time series assumptions, many interactions in neuroscience and economics applications are nonlinea…
A Unified Framework for Long Range and Cold Start Forecasting of Seasonal Profiles in Time Series
Christopher Xie, Alex Tank, Alec Greaves-Tunnell +1
Providing long-range forecasts is a fundamental challenge in time series modeling, which is only compounded by the challenge of having to form such forecasts when a time series has…
Granger Causality Networks for Categorical Time Series
Alex Tank, Emily B. Fox, Ali Shojaie
We present a new framework for learning Granger causality networks for multivariate categorical time series, based on the mixture transition distribution (MTD) model. Traditionally…
Identifiability and Estimation of Structural Vector Autoregressive Models for Subsampled and Mixed Frequency Time Series
Alex Tank, Emily B. Fox, Ali Shojaie
Causal inference in multivariate time series is challenging due to the fact that the sampling rate may not be as fast as the timescale of the causal interactions. In this context,…