Search Results for author: Tülay Adalı

Found 9 papers, 2 papers with code

Independent Vector Extraction Constrained on Manifold of Half-Length Filters

no code implementations4 Apr 2023 Zbyněk Koldovský, Jaroslav Čmejla, Tülay Adalı, Stephen O'Regan

In this paper, we propose a mixing model for joint blind source extraction where the mixing model parameters are linked across the frequencies.

Speaker Separation

Coupled CP tensor decomposition with shared and distinct components for multi-task fMRI data fusion

no code implementations25 Nov 2022 Ricardo Augusto Borsoi, Isabell Lehmann, Mohammad Abu Baker Siddique Akhonda, Vince Calhoun, Konstantin Usevich, David Brie, Tülay Adalı

Discovering components that are shared in multiple datasets, next to dataset-specific features, has great potential for studying the relationships between different subjects or tasks in functional Magnetic Resonance Imaging (fMRI) data.

Tensor Decomposition

An AO-ADMM approach to constraining PARAFAC2 on all modes

1 code implementation4 Oct 2021 Marie Roald, Carla Schenker, Vince D. Calhoun, Tülay Adalı, Rasmus Bro, Jeremy E. Cohen, Evrim Acar

We also apply our model to two real-world datasets from neuroscience and chemometrics, and show that constraining the evolving mode improves the interpretability of the extracted patterns.

Tracing Network Evolution Using the PARAFAC2 Model

1 code implementation23 Oct 2019 Marie Roald, Suchita Bhinge, Chunying Jia, Vince Calhoun, Tülay Adalı, Evrim Acar

For instance, how spatial networks of functional connectivity in the brain evolve during a task is not well-understood.

Tensor-Based Fusion of EEG and FMRI to Understand Neurological Changes in Schizophrenia

no code implementations7 Dec 2016 Evrim Acar, Yuri Levin-Schwartz, Vince D. Calhoun, Tülay Adalı

Neuroimaging modalities such as functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) provide information about neurological functions in complementary spatiotemporal resolutions; therefore, fusion of these modalities is expected to provide better understanding of brain activity.

EEG Electroencephalogram (EEG)

Linked Component Analysis from Matrices to High Order Tensors: Applications to Biomedical Data

no code implementations29 Aug 2015 Guoxu Zhou, Qibin Zhao, Yu Zhang, Tülay Adalı, Shengli Xie, Andrzej Cichocki

With the increasing availability of various sensor technologies, we now have access to large amounts of multi-block (also called multi-set, multi-relational, or multi-view) data that need to be jointly analyzed to explore their latent connections.

Tensor Decomposition

Independent Vector Analysis: Identification Conditions and Performance Bounds

no code implementations29 Mar 2013 Matthew Anderson, Geng-Shen Fu, Ronald Phlypo, Tülay Adalı

Thus, we provide the additional conditions for when the arbitrary ordering of the sources within each dataset is common.

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