AIMC Topic: Markov Chains

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Synchronization for stochastic coupled networks with Lévy noise via event-triggered control.

Neural networks : the official journal of the International Neural Network Society Mar 24, 2021
This paper addresses the realization of almost sure synchronization problem for a new array of stochastic networks associated with delay and Lévy noise via event-triggered control. The coupling structure of the network is governed by a continuous-tim...
Time Factors Markov Chains Stochastic Processes Neural Networks, Computer
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Synchronization criteria of delayed inertial neural networks with generally Markovian jumping.

Neural networks : the official journal of the International Neural Network Society Feb 24, 2021
In this paper, the synchronization problem of inertial neural networks with time-varying delays and generally Markovian jumping is investigated. The second order differential equations are transformed into the first-order differential equations by ut...
Markov Chains Pattern Recognition, Automated Algorithms Time Factors Uncertainty Neural Networks, Computer
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Statistical foundation of Variational Bayes neural networks.

Neural networks : the official journal of the International Neural Network Society Feb 5, 2021
Despite the popularism of Bayesian neural networks (BNNs) in recent years, its use is somewhat limited in complex and big data situations due to the computational cost associated with full posterior evaluations. Variational Bayes (VB) provides a usef...
Bayes Theorem Markov Chains Monte Carlo Method Machine Learning
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Creating artificial human genomes using generative neural networks.

PLoS genetics Feb 4, 2021
Generative models have shown breakthroughs in a wide spectrum of domains due to recent advancements in machine learning algorithms and increased computational power. Despite these impressive achievements, the ability of generative models to create re...
Genome, Human Databases, Factual Computer Simulation Population Polymorphism, Single Nucleotide Chromosomes, Human, Pair 15 HapMap Project Databases, Genetic Deep Learning Machine Learning Alleles Humans Algorithms Markov Chains Neural Networks, Computer
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Resilient asynchronous state estimation of Markov switching neural networks: A hierarchical structure approach.

Neural networks : the official journal of the International Neural Network Society Dec 8, 2020
This paper deals with the issue of resilient asynchronous state estimation of discrete-time Markov switching neural networks. Randomly occurring signal quantization and packet dropout are involved in the imperfect measured output. The asynchronous sw...
Neural Networks, Computer Deep Learning Markov Chains Resilience, Psychological
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Approximating the Ideal Observer for Joint Signal Detection and Localization Tasks by use of Supervised Learning Methods.

IEEE transactions on medical imaging Nov 30, 2020
Medical imaging systems are commonly assessed and optimized by use of objective measures of image quality (IQ). The Ideal Observer (IO) performance has been advocated to provide a figure-of-merit for use in assessing and optimizing imaging systems be...
ROC Curve Image Processing, Computer-Assisted Monte Carlo Method Normal Distribution Supervised Machine Learning Markov Chains
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Synchronization of Coupled Time-Delay Neural Networks With Mode-Dependent Average Dwell Time Switching.

IEEE transactions on neural networks and learning systems Nov 30, 2020
In the literature, the effects of switching with average dwell time (ADT), Markovian switching, and intermittent coupling on stability and synchronization of dynamic systems have been extensively investigated. However, all of them are considered sepa...
Algorithms Probability Stochastic Processes Neural Networks, Computer Markov Chains
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Stochastic Finite-Time H State Estimation for Discrete-Time Semi-Markovian Jump Neural Networks With Time-Varying Delays.

IEEE transactions on neural networks and learning systems Nov 30, 2020
In this article, the finite-time H state estimation problem is addressed for a class of discrete-time neural networks with semi-Markovian jump parameters and time-varying delays. The focus is mainly on the design of a state estimator such that the co...
Stochastic Processes Finite Element Analysis Algorithms Markov Chains Neural Networks, Computer
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DeepFRET, a software for rapid and automated single-molecule FRET data classification using deep learning.

eLife Nov 3, 2020
Single-molecule Förster Resonance energy transfer (smFRET) is an adaptable method for studying the structure and dynamics of biomolecules. The development of high throughput methodologies and the growth of commercial instrumentation have outpaced the...
False Positive Reactions Single Molecule Imaging Normal Distribution Markov Chains Fluorescence Resonance Energy Transfer Algorithms Fluorescent Dyes Molecular Dynamics Simulation Software Signal Processing, Computer-Assisted Deep Learning Reproducibility of Results Nanotechnology User-Computer Interface Kinetics
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Reward-predictive representations generalize across tasks in reinforcement learning.

PLoS computational biology Oct 15, 2020
In computer science, reinforcement learning is a powerful framework with which artificial agents can learn to maximize their performance for any given Markov decision process (MDP). Advances over the last decade, in combination with deep neural netwo...
Animals Algorithms Reinforcement, Psychology Task Performance and Analysis Brain Reward Models, Psychological Humans Markov Chains Neural Networks, Computer
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