469 citations · 2k across the 43 of their papers we have counts for
9 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…
sgmcmc: An R Package for Stochastic Gradient Markov Chain Monte Carlo
Jack Baker, Paul Fearnhead, Emily B. Fox +1
This paper introduces the R package sgmcmc; which can be used for Bayesian inference on problems with large datasets using stochastic gradient Markov chain Monte Carlo (SGMCMC). Tr…
Dynamics of homelessness in urban America
Chris Glynn, Emily B. Fox
The relationship between housing costs and homelessness has important implications for the way that city and county governments respond to increasing homeless populations. Though m…
Stochastic Gradient MCMC Methods for Hidden Markov Models
Yi-An Ma, Nicholas J. Foti, Emily B. Fox
Stochastic gradient MCMC (SG-MCMC) algorithms have proven useful in scaling Bayesian inference to large datasets under an assumption of i.i.d data. We instead develop an SG-MCMC al…