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Monte Carlo Method

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Emergence of low noise frustrated states in E/I balanced neural networks.

Neural networks : the official journal of the International Neural Network Society
We study emerging phenomena in binary neural networks where, with a probability c synaptic intensities are chosen according with a Hebbian prescription, and with probability (1-c) there is an extra random contribution to synaptic weights. This new te...

Artificial neural network (ANN)-based prediction of depth filter loading capacity for filter sizing.

Biotechnology progress
This article presents an application of artificial neural network (ANN) modelling towards prediction of depth filter loading capacity for clarification of a monoclonal antibody (mAb) product during commercial manufacturing. The effect of operating pa...

A Fuzzy Permutation Method for False Discovery Rate Control.

Scientific reports
Biomedical researchers often encounter the large-p-small-n situations-a great number of variables are measured/recorded for only a few subjects. The authors propose a fuzzy permutation method to address the multiple testing problem for small sample s...

Co-combustion of peanut hull and coal blends: Artificial neural networks modeling, particle swarm optimization and Monte Carlo simulation.

Bioresource technology
Co-combustion of coal and peanut hull (PH) were investigated using artificial neural networks (ANN), particle swarm optimization, and Monte Carlo simulation as a function of blend ratio, heating rate, and temperature. The best prediction was reached ...

A hierarchical model for integrating unsupervised generative embedding and empirical Bayes.

Journal of neuroscience methods
BACKGROUND: Generative models of neuroimaging data, such as dynamic causal models (DCMs), are commonly used for inferring effective connectivity from individual subject data. Recently introduced "generative embedding" approaches have used DCM-based c...

A class of joint models for multivariate longitudinal measurements and a binary event.

Biometrics
Predicting binary events such as newborns with large birthweight is important for obstetricians in their attempt to reduce both maternal and fetal morbidity and mortality. Such predictions have been a challenge in obstetric practice, where longitudin...

NEURAL NETWORK MODELLING OF CARDIAC DOSE CONVERSION COEFFICIENT FOR ARBITRARY X-RAY SPECTRA.

Radiation protection dosimetry
In this article, an approach to compute the dose conversion coefficients (DCCs) is described for the computational voxel phantom 'High-Definition Reference Korean-Man' (HDRK-Man) using artificial neural networks (ANN). For this purpose, the voxel pha...

Firing rate dynamics in recurrent spiking neural networks with intrinsic and network heterogeneity.

Journal of computational neuroscience
Heterogeneity of neural attributes has recently gained a lot of attention and is increasing recognized as a crucial feature in neural processing. Despite its importance, this physiological feature has traditionally been neglected in theoretical studi...

Recent Advances in General Game Playing.

TheScientificWorldJournal
The goal of General Game Playing (GGP) has been to develop computer programs that can perform well across various game types. It is natural for human game players to transfer knowledge from games they already know how to play to other similar games. ...