Pages that link to "Item:Q389932"

The following pages link to Analyzing complex functional brain networks: fusing statistics and network science to understand the brain (Q389932):

Displaying 25 items.

• A signal-processing-based approach to time-varying graph analysis for dynamic brain network identification (Q454658) (← links)
• Voxel scale complex networks of functional connectivity in the rat brain: neurochemical state dependence of global and local topological properties (Q454696) (← links)
• Statistical challenges of big brain network data (Q1642385) (← links)
• Complex brain network analysis and its applications to brain disorders: a survey (Q1687457) (← links)
• Bayesian inference and testing of group differences in brain networks (Q1752001) (← links)
• Online network monitoring (Q2066715) (← links)
• A Python hands-on tutorial on network and topological neuroscience (Q2117924) (← links)
• A random effects stochastic block model for joint community detection in multiple networks with applications to neuroimaging (Q2194484) (← links)
• Exponential-family models of random graphs: inference in finite, super and infinite population scenarios (Q2225321) (← links)
• Model-free two-sample test for network-valued data (Q2291338) (← links)
• Convergence of covariance and spectral density estimates for high-dimensional locally stationary processes (Q2656594) (← links)
• An analysis of age-related alterations in functional memory networks (Q2902540) (← links)
• Googling the brain: discovering hierarchical and asymmetric network structures, with applications in neuroscience (Q2909123) (← links)
• Exploring dependence structures in the international arms trade network: A network autocorrelation approach (Q3386465) (← links)
• Identifying functional co‐activation patterns in neuroimaging studies via poisson graphical models (Q3465358) (← links)
• Understanding principles of integration and segregation using whole-brain computational connectomics: implications for neuropsychiatric disorders (Q4560662) (← links)
• THE AVERAGE WEIGHTED PATH LENGTH FOR A CLASS OF HIERARCHICAL NETWORKS (Q5122205) (← links)
• (Q5471689) (← links)
• A Bayesian hierarchical framework for modeling brain connectivity for neuroimaging data (Q5739290) (← links)
• Topological dissimilarities of hierarchical resting networks in type 2 diabetes mellitus and obesity (Q6172470) (← links)
• Flexible parametrization of graph-theoretical features from individual-specific networks for prediction (Q6615905) (← links)
• Review of weighted exponential random graph models frameworks applied to neuroimaging (Q6618399) (← links)
• Detecting associations between intact connectomes and clinical covariates using recursive partitioning object-oriented data analysis (Q6627196) (← links)
• Relative rate of change in cognitive score network dynamics via Bayesian hierarchical models reveal spatial patterns of neurodegeneration (Q6627539) (← links)
• Asymptotic distribution of the friendship paradox of a random geometric graph (Q6654886) (← links)