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Markov Brains: A Technical Introduction
[article]
2017
arXiv
pre-print
Markov Brains are a class of evolvable artificial neural networks (ANN). ...
Here we describe in detail how a Markov Brain works, what techniques can be used to study them, and how they can be evolved. ...
As a consequence, each row of the matrix P
needs to sum to 1.0:
In this report we use a capital B for brains that are specifically artificial brains of the Markov type. ...
arXiv:1709.05601v1
fatcat:egzd3g76sfbazifnzvm5yxn3vy
Markov Blankets in the Brain
[article]
2020
arXiv
pre-print
Recent characterisations of self-organising systems depend upon the presence of a Markov blanket: a statistical boundary that mediates the interactions between what is inside of and outside of a system ...
This depends upon the dynamic coupling between functional units, whose form recapitulates that of a Markov blanket at each level. ...
Introduction Scientific investigation in neurobiology often begins -perhaps only implicitly -by partitioning the brain into functional units. ...
arXiv:2006.02741v1
fatcat:w7vv2ndzajea7crwdivndamy3q
The Emperor's New Markov Blankets
2021
Behavioral and Brain Sciences
We then identify a persistent confusion in the literature between the formal use of Markov blankets as an epistemic tool for Bayesian inference, and their novel metaphysical use in the free energy framework ...
We suggest that this literature would do well in differentiating between two different research programs: 'inference with a model' and 'inference within a model'. ...
are listed in the introduction). ...
doi:10.1017/s0140525x21002351
pmid:34674782
fatcat:splnqu7npnhvhhu73ra3szyl3e
Parcels and particles: Markov blankets in the brain
[article]
2020
arXiv
pre-print
It is predicated on the notion of Markov blankets that play a fundamental role in the self-organisation of far from equilibrium systems. ...
As such, it offers a way of linking dynamics on directed graphs to the phenomenology of intrinsic brain networks. ...
Because this paper is a technical (foundational) description of the procedures entailed by the existence of Markov blanketsof Markov blanketswe have focused on the simplest implementation. ...
arXiv:2007.09704v1
fatcat:akmutwfnercjfcdwrt3i5sd3iu
Markov random field segmentation of brain MR images
1997
IEEE Transactions on Medical Imaging
We describe a fully-automatic 3D-segmentation technique for brain MR images. ...
A simulated annealing and an iterated conditional modes implementation are presented. Keywords: Magnetic Resonance Imaging, Segmentation, Markov Random Fields ...
Tellmann for their advice and technical assistance. They would also like to thank J. Shah for assistance in preparing the manuscript. ...
doi:10.1109/42.650883
pmid:9533587
fatcat:ullbj73mbbabhc7y24snla7n34
Parcels and particles: Markov blankets in the brain
2020
Network Neuroscience
It is predicated on the notion of Markov blankets that play a fundamental role in the self-organization of far from equilibrium systems. ...
As such, it offers a way of linking dynamics on directed graphs to the phenomenology of intrinsic brain networks. ...
Because this paper is a technical (foundational) description of the procedures entailed by the existence of Markov blankets, we have focused on the simplest implementation. ...
doi:10.1162/netn_a_00175
pmid:33688613
pmcid:PMC7935044
fatcat:gshs2lvrezeaffys6nl3kpj2bm
Markov chain Monte Carlo methods for hierarchical clustering of dynamic causal models
2021
Human Brain Mapping
brain connectivity. ...
In this article, we address technical difficulties that arise when applying Markov chain Monte Carlo (MCMC) to hierarchical models designed to perform clustering in the space of latent parameters of subject-wise ...
This technical note addresses the specific problem of applying Markov chain Monte Carlo (MCMC) to hierarchical clustering in the context of generative embedding (GE) . ...
doi:10.1002/hbm.25431
pmid:33826194
pmcid:PMC8193526
fatcat:22vsdofe7fg2zl5nebdqdmmwua
Verifying Reachability Properties in Markov Chains via Incremental Induction
[article]
2019
arXiv
pre-print
Markov chains. ...
There is a scalability gap between probabilistic and non-probabilistic verification. ...
The technical contributions in this paper are: -In Section 3 we present an algorithm for verifying reachability properties in Markov chains, which uses incrementally constructed inductive invariants to ...
arXiv:1909.08017v2
fatcat:uqa3ll4glnhndemhfine2hrl2q
Semi-Markov and hidden semi-Markov models of energy systems
2018
E3S Web of Conferences
The possibilities of application of semi-Markov processes with common phase space of states, hidden Markov and semi-Markov models for energy system modeling are considered in the paper. ...
, hidden semi-Markov models, their application for energy system modelling Semi-Markov processes are widely used to construct models and analyse systems of different purposes: technical, production, energy ...
Introduction According to the road map of National Technology Initiative "EnergyNet" between the main purposes of this project are: 1." ...
doi:10.1051/e3sconf/20185802023
fatcat:5n6qkckmorehbmkkxu7ijuotz4
Client-Centred Music Imagery Classification Based on Hidden Markov Models of Baseline Prefrontal Hemodynamic Response
[chapter]
2013
Brain-Computer Interface Systems - Recent Progress and Future Prospects
Hidden Markov models A hidden Markov model is a statistical model which examines a Markov process wherein the observable outputs are dependent upon the unobservable states. ...
Client-Centred Music Imagery Classification Based on Hidden Markov Models ... http://dx.doi.org/10.5772/55804
Brain-Computer Interface Systems -Recent Progress and Future Prospects ...
doi:10.5772/55804
fatcat:gle6m7zhanh6jf5vu6lonn4ity
Region Detection in Markov Random Fields: Gaussian Case
[article]
2018
arXiv
pre-print
We consider the problem of model selection in Gaussian Markov fields in the sample deficient scenario. ...
bounds and show that a bounded number of samples can be sufficient to consistently recover these regions. ...
INTRODUCTION
A. ...
arXiv:1802.03848v8
fatcat:v6i4yspchjbz7km5vioaj2k4wu
Context-Aware Hidden Markov Models of Jazz Music with Variable Markov Oracle
2017
Zenodo
The proposed latent variable model is a multi-level Hidden Markov Model (HMM) extracted from the VMO, and is called the VMO-HMM. ...
In this paper, a latent variable model based on the Variable Markov Oracle (VMO) is proposed to capture long-term temporal relationships between sequential observations. ...
The technical details of constructing a VMO could be found in (Wang, Hsu, and Dubnov 2016) and are not repeated here. ...
doi:10.5281/zenodo.4285246
fatcat:cgpfd52jpzgebnbx2v2rirylzm
Unsupervised learning and mapping of active brain functional MRI signals based on hidden semi-Markov event sequence models
2005
IEEE Transactions on Medical Imaging
In this paper, a novel functional magnetic resonance imaging (fMRI) brain mapping method is presented within the statistical modeling framework of hidden semi-Markov event sequence models (HSMESMs). ...
Index Terms-Brain mapping, functional MRI, hidden Markov models, signal processing, wavelet transform. ...
INTRODUCTION C OMMONLY used techniques in functional MRI (fMRI) brain mapping can be divided into two classes: data-driven and model-driven. ...
doi:10.1109/tmi.2004.841225
pmid:15707252
fatcat:fhlkgeuciradlbrx2wyt7mg3ii
Continuous-Time Markov Chains
[chapter]
2016
Introduction to Stochastic Processes With R
Introduction We now turn to continuous-time Markov chains (CTMC's), which are a natural sequel to the study of discrete-time Markov chains (DTMC's), the Poisson process and the exponential distribution ...
(Pooh Bear and the Three Honey Trees) A bear of little brain named Pooh is fond of honey. Bees producing honey are located in three trees: tree A, tree B and tree C. ...
doi:10.1002/9781118740712.ch7
fatcat:55dijthetrh3dpjo7scxlvvgmy
Markovian Segmentation of Brain Tumor MRI Images
2017
International Journal of Informatics and Communication Technology (IJ-ICT)
These algorithms are used to segment brain tumor Magnetic Resonance Imaging (MRI) images, under Hidden Markov Chain with Indepedant Noise (HMC-IN). ...
<p>Image segmentation is a fundamental operation in image processing, which consists to di-vide an image in the homogeneous region for helping a human to analyse image, to diagnose a disease and take the ...
We are used MPM Algorithm [5] to estimate a final configuration of X. Also, we extract a brain tumor using thresholding technic [11] . ...
doi:10.11591/ijict.v6i3.pp155-165
fatcat:aadysvicbjebfhl6hfikp6qceq
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