3 code implementations • 16 Feb 2018 • Alex Tank, Ian Covert, Nicholas Foti, Ali Shojaie, Emily Fox
We show that our neural Granger causality methods outperform state-of-the-art nonlinear Granger causality methods on the DREAM3 challenge data.
1 code implementation • 22 Nov 2017 • Alex Tank, Ian Cover, Nicholas J. Foti, Ali Shojaie, Emily B. Fox
A sufficient condition for Granger non-causality in this setting is that all of the outgoing weights of the input data, the past lags of a series, to the first hidden layer are zero.
no code implementations • 22 Nov 2017 • 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 regions.
no code implementations • 23 Oct 2017 • Christopher Xie, Alex Tank, Alec Greaves-Tunnell, Emily Fox
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 never previously been observed.
no code implementations • 1 Dec 2014 • Alex Tank, Nicholas J. Foti, Emily B. Fox
In theory, Bayesian nonparametric (BNP) models are well suited to streaming data scenarios due to their ability to adapt model complexity with the observed data.