Factorization of Separable and Patterned Covariance Matrices for Gibbs Sampling. - Daniel B. Rowe (Monte Carlo Methods Appl., 2000)

Jointly Distributed Mean and Mixing Coefficients for Bayesian Source Separation using MCMC and ICM. - Daniel B. Rowe (Monte Carlo Methods Appl., 2002)

Significant FMRI Neurologic Synchrony Using Monte Carlo Methods. - Daniel B. Rowe (Monte Carlo Methods Appl., 2003)

An evaluation of thresholding techniques in fMRI analysis. - Brent R. Logan; Daniel B. Rowe (NeuroImage, 2004)

A complex way to compute fMRI activation. - Daniel B. Rowe; Brent R. Logan (NeuroImage, 2004)

Parameter estimation in the magnitude-only and complex-valued fMRI data models. - Daniel B. Rowe (NeuroImage, 2005)

Modeling both the magnitude and phase of complex-valued fMRI data. - Daniel B. Rowe (NeuroImage, 2005)

Complex fMRI analysis with unrestricted phase is equivalent to a magnitude-only model. - Daniel B. Rowe; Brent R. Logan (NeuroImage, 2005)

Processing the acute cocaine FMRI response in human brain with Bayesian source separation. - Peter R. Kufahl; Daniel B. Rowe; Shi-Jiang Li (Digit. Signal Process., 2007)

Reducing the unwanted draining vein BOLD contribution in fMRI with statistical post-processing methods. - Andrew S. Nencka; Daniel B. Rowe (NeuroImage, 2007)

Improving robustness and reliability of phase-sensitive fMRI analysis using temporal off-resonance alignment of single-echo timeseries (TOAST). - Andrew D. Hahn; Andrew S. Nencka; Daniel B. Rowe (NeuroImage, 2009)

Physiologic noise regression, motion regression, and TOAST dynamic field correction in complex-valued fMRI time series. - Andrew D. Hahn; Daniel B. Rowe (NeuroImage, 2012)

Quantification of the Statistical Effects of Spatiotemporal Processing of Nontask fMRI Data. - Müge Karaman; Andrew S. Nencka; Iain P. Bruce; Daniel B. Rowe (Brain Connect., 2014)

Quantifying the Statistical Impact of GRAPPA in fcMRI Data With a Real-Valued Isomorphism. - Iain P. Bruce; Daniel B. Rowe (IEEE Trans. Medical Imaging, 2014)

Impacts of simultaneous multislice acquisition on sensitivity and specificity in fMRI. - Benjamin B. Risk; Mary C. Kociuba; Daniel B. Rowe (NeuroImage, 2018)

Graph Convolutional Networks for Model-Based Learning in Nonlinear Inverse Problems. - William Herzberg; Daniel B. Rowe; Andreas Hauptmann; Sarah Jane Hamilton (IEEE Trans. Computational Imaging, 2021)

Pruning a neural network using Bayesian inference. - Sunil Mathew; Daniel B. Rowe (CoRR, 2023)

Generation of patient specific cardiac chamber models using generative neural networks under a Bayesian framework for electroanatomical mapping. - Sunil Mathew; Jasbir Sra; Daniel B. Rowe (CoRR, 2023)