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Ivor Cribben
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2020 – today
- 2024
- [j11]Martin Ondrus
, Ivor Cribben:
fabisearch: A package for change point detection in and visualization of the network structure of multivariate high-dimensional time series in R. Neurocomputing 578: 127321 (2024) - [c1]Dorcas Ofori-Boateng, Jaidev Goel, Ivor Cribben, Yulia R. Gel:
Graphical Model-Based Lasso for Weakly Dependent Time Series of Tensors. ECML/PKDD (5) 2024: 249-264 - 2023
- [j10]Xin Xiong
, Ivor Cribben:
Beyond Linear Dynamic Functional Connectivity: A Vine Copula Change Point Model. J. Comput. Graph. Stat. 32(3): 853-872 (2023) - 2022
- [j9]Andreas Anastasiou, Ivor Cribben, Piotr Fryzlewicz:
Cross-covariance isolate detect: A new change-point method for estimating dynamic functional connectivity. Medical Image Anal. 75: 102252 (2022) - 2021
- [j8]Mostafa Rezaei, Ivor Cribben, Michele Samorani
:
A clustering-based feature selection method for automatically generated relational attributes. Ann. Oper. Res. 303(1): 233-263 (2021) - [j7]Dorcas Ofori-Boateng, Yulia R. Gel, Ivor Cribben:
Nonparametric Anomaly Detection on Time Series of Graphs. J. Comput. Graph. Stat. 30(3): 756-767 (2021) - 2020
- [j6]Wojciech Pietrasik, Ivor Cribben, Fraser Olsen, Yushan Huang, Nikolai V. Malykhin
:
Diffusion tensor imaging of the corpus callosum in healthy aging: Investigating higher order polynomial regression modelling. NeuroImage 213: 116675 (2020)
2010 – 2019
- 2018
- [j5]Yunan Zhu, Ivor Cribben:
Sparse Graphical Models for Functional Connectivity Networks: Best Methods and the Autocorrelation Issue. Brain Connect. 8(3): 139-165 (2018) - [j4]Brian Hart, Ivor Cribben, Mark Fiecas
, Alzheimer's Disease Neuroimaging Initiative:
A longitudinal model for functional connectivity networks using resting-state fMRI. NeuroImage 178: 687-701 (2018) - 2017
- [j3]Mark Fiecas, Ivor Cribben, Reyhaneh Bakhtiari
, Jacqueline Cummine:
A variance components model for statistical inference on functional connectivity networks. NeuroImage 149: 256-266 (2017) - 2013
- [j2]Ivor Cribben, Tor D. Wager, Martin A. Lindquist:
Detecting functional connectivity change points for single-subject fMRI data. Frontiers Comput. Neurosci. 7: 143 (2013) - 2012
- [j1]Ivor Cribben, Ragnheidur Haraldsdottir, Lauren Y. Atlas
, Tor D. Wager, Martin A. Lindquist:
Dynamic connectivity regression: Determining state-related changes in brain connectivity. NeuroImage 61(4): 907-920 (2012)
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last updated on 2024-09-09 01:16 CEST by the dblp team
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