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stat.ME2026
Credible rectangles for high-dimensional posterior comparison
Alice Chevaux, Julyan Arbel, Guillaume Kon Kam King +1
We propose a Bayesian framework for uncertainty quantification and comparison in brain connectivity graph analysis. Standard graph-based approaches typically rely on point estimate…
stat.ME2026
Prior elicitation for Bayesian estimation of single-subject connectivity networks
Yiye Jiang, Alice Chevaux, Wendy Meiring +4
Inference of brain functional connectivity networks from resting-state fMRI data is a key focus in neuroimaging. This paper introduces new Bayesian approaches for inferring a funct…
stat.ME2025
Benchmarking Brain Connectivity Graph Inference: A Novel Validation Approach
Alice Chevaux, Ali Fahkar, Kévin Polisano +2
Inferring a binary connectivity graph from resting-state fMRI data for a single subject requires making several methodological choices and assumptions that can significantly affect…