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20152026
most citedTopological Data Analysis for Multivariate Time Series Data

33 citations · 108 across the 70 of their papers we have counts for

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Showing 2019Show all

5 papers · 1 filter

stat.ME2019

Modeling Spectral Properties in Stationary Processes of Varying Dimensions with Applications to Brain Local Field Potential Signals

Raanju Ragavendar Sundararajan, Ron D. Frostig, Hernando Ombao

A common class of methods for analyzing of multivariate time series, stationary and nonstationary, decomposes the observed series into latent sources. Methods such as principal com…

stat.ME2019

Shape-Preserving Prediction for Stationary Functional Time Series

Shuhao Jiao, Hernando Ombao

This article presents a novel method for prediction of stationary functional time series, in particular for trajectories that share a similar pattern but display variable phases. T…

stat.ME2019

Functional time series prediction under partial observation of the future curve

Shuhao Jiao, Alexander Aue, Hernando Ombao

This paper tackles one of the most fundamental goals in functional time series analysis which is to provide reliable predictions for future functions. Existing methods for predicti…

stat.ME2019

Modeling Dynamic Functional Connectivity with Latent Factor Gaussian Processes

Lingge Li, Dustin Pluta, Babak Shahbaba +3

Dynamic functional connectivity, as measured by the time-varying covariance of neurological signals, is believed to play an important role in many aspects of cognition. While many…

cs.LG2019

Classification of EEG-Based Brain Connectivity Networks in Schizophrenia Using a Multi-Domain Connectome Convolutional Neural Network

Chun-Ren Phang, Chee-Ming Ting, Fuad Noman +1

We exploit altered patterns in brain functional connectivity as features for automatic discriminative analysis of neuropsychiatric patients. Deep learning methods have been introdu…