Results 31 to 40 of about 65,094 (251)
Bayesian artificial brain with ChatGPT
CoRR, 2023 This paper aims to investigate the mathematical problem-solving capabilities of Chat Generative Pre-Trained Transformer (ChatGPT) in case of Bayesian reasoning. The study draws inspiration from Zhu & Gigerenzer's research in 2006, which posed the question: Can children reason the Bayesian way?
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To integrate or not to integrate: Temporal dynamics of hierarchical Bayesian causal inference.
PLoS Biology, 2019 To form a percept of the environment, the brain needs to solve the binding problem-inferring whether signals come from a common cause and are integrated or come from independent causes and are segregated.
Máté Aller, Uta Noppeney
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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
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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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BAYESIAN SENSE OF TIME IN BIOLOGICAL AND ARTIFICIAL BRAINS
, 2023 Enquiries concerning the underlying mechanisms and the emergent properties of a biological brain have a long history of theoretical postulates and experimental findings. Today, the scientific community tends to converge to a single interpretation of the brain's cognitive underpinnings -- that it is a Bayesian inference machine.
Zafeirios Fountas, Alexey Zakharov
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Cortical hierarchies perform Bayesian causal inference in multisensory perception.
PLoS Biology, 2015 To form a veridical percept of the environment, the brain needs to integrate sensory signals from a common source but segregate those from independent sources.
Tim Rohe, Uta Noppeney
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Brain dynamics for confidence-weighted learning.
PLoS Computational Biology, 2020 Learning in a changing, uncertain environment is a difficult problem. A popular solution is to predict future observations and then use surprising outcomes to update those predictions.
Florent Meyniel
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Brain-Inspired Hardware Solutions for Inference in Bayesian Networks
Frontiers in Neuroscience, 2021 The implementation of inference (i.e., computing posterior probabilities) in Bayesian networks using a conventional computing paradigm turns out to be inefficient in terms of energy, time, and space, due to the substantial resources required by floating ...
Leila Bagheriye, Johan Kwisthout
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