Results 41 to 50 of about 2,095,528 (293)
Approximate Bayesian inference for doubly robust estimation [PDF]
, 2015 Doubly robust estimators are typically constructed by combining outcome regression and propensity score models to satisfy moment restrictions that ensure consistent estimation of causal quantities provided at least one of the component models is ...
McCoy, EJ, Graham, DJ, Stephens, DA
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Simulation-Based Calibration Checking for Bayesian Computation: The Choice of Test Quantities Shapes Sensitivity [PDF]
, 2023 Simulation-based calibration checking (SBC) is a practical method to validate computationally-derived posterior distributions or their approximations. In this paper, we introduce a new variant of SBC to alleviate several known problems.
Shinyoung, Kim +9 more
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Bayesian multi-modal model comparison: a case study on the generators of the spike and the wave in generalized spike–wave complexes [PDF]
, 2010 We present a novel approach to assess the networks involved in the generation of spontaneous pathological brain activity based on multi-modal imaging data.
Lemieux, L. +8 more
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Objective Bayesian fMRI analysis - a pilot study in different clinical environments
Frontiers in Neuroscience, 2015 Functional MRI (fMRI) used for neurosurgical planning delineates functionally eloquent brain areas by time-series analysis of task-induced BOLD signal changes. Commonly used frequentist statistics protect against false positive results based on a p-value
Joerg eMagerkurth +15 more
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Bayesian Models of Brain and Behaviour [PDF]
ISRN Biomathematics, 2012 This paper presents a review of Bayesian models of brain and behaviour. We first review the basic principles of Bayesian inference. This is followed by descriptions of sampling and variational methods for approximate inference, and forward and backward recursions in time for inference in dynamical models. The review of behavioural models covers work in
openaire +1 more source
Bayesian Solution Uncertainty Quantification for Differential Equations [PDF]
, 2016 We explore probability modelling of discretization uncertainty for system states defined implicitly by ordinary or partial differential equations. Accounting for this uncertainty can avoid posterior under-coverage when likelihoods are constructed from a ...
Girolami, MA +4 more
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Comparing Bayesian and non-Bayesian accounts of human confidence reports. [PDF]
PLoS Computational Biology, 2018 Humans can meaningfully report their confidence in a perceptual or cognitive decision. It is widely believed that these reports reflect the Bayesian probability that the decision is correct, but this hypothesis has not been rigorously tested against non ...
William T Adler, Wei Ji Ma
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NeuroImage, 2022 The general linear model (GLM) is a widely popular and convenient tool for estimating the functional brain response and identifying areas of significant activation during a task or stimulus.
Daniel Spencer +4 more
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Music and the brain: disorders of musical listening [PDF]
, 2006 The study of the brain bases for normal musical listening has advanced greatly in the last 30 years. The evidence from basic and clinical neuroscience suggests that listening to music involves many cognitive components with distinct brain substrates ...
Stewart, Lauren +14 more
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fMRI activation detection with EEG priors [PDF]
, 2013 The purpose of brain mapping techniques is to advance the understanding of the relationship between structure and function in the human brain in so-called activation studies.
Sämann, Philipp +3 more
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