1 citations · 2 across the 16 of their papers we have counts for
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Partial Wavelet Canonical Coherence for Nonstationary Signals with High Dimensional Confounders
Haibo Wu, Marina I. Knight, Hernando Ombao
We develop Partial Wavelet Canonical Coherence for measuring the direct canonical association between two multivariate nonstationary time series after adjustment for possibly high-…
Dynamic cross-scale wavelet coherence
Haibo Wu, Marina I. Knight, Hernando Ombao
This paper develops a novel statistical approach that allows for the {\em first time} the {\em cross}-oscillatory characterisation of temporally localised interactions between chan…
Topological Effective Connectivity Modeling in Brain Networks
Anass El-Yaagoubi, Moo K. Chung, Hernando Ombao
Characterizing directed information flow in brain networks is difficult because neural circuits are full of recurrent feedback loops. Many existing tools for directed dependence as…
Filtration-Based Learning of Multiscale Shared Structures for Multiple Functional Predictors
Shuhao Jiao, Hernando Ombao, Ian W. McKeague
It is crucial to learn the shared structures among functional predictors, as these structures characterize how predictor components exert common effects and, more generally, how pr…
Forecasting Multivariate Time Series under Predictive Heterogeneity: A Validation-Driven Clustering Framework
Ziling Ma, Ãngel López Oriona, Hernando Ombao +1
We study adaptive pooling under predictive heterogeneity in high-dimensional multivariate time series forecasting, where global models improve statistical efficiency but may fail t…
Wavelet Canonical Coherence for Nonstationary Signals
Haibo Wu, Marina I. Knight, Keiland W. Cooper +2
Understanding the evolving dependence between two clusters of multivariate signals is fundamental in neuroscience and other domains where sub-networks in a system interact dynamica…