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44 406 (0,172s)

Result

On the Bayesian Interpretation of Robust Regression Neural Networks

, regularized neural networks are explained to correspond to the Bayesian approach obtained neural networks with available prior information, i.e. a likelihood-based perspective of training neural...

Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

  • 2024
  • D
  • Link
Result

On the Accuracy of Copula-based Bayesian Classifiers: An Experimental Comparison with Neural Networks

is a copula-based Bayesian classifier based on elliptical and Archimedean copulas. The remaining two are Naive Bayes and Neural Networks. Such a comparison, particularly for the recently proposed Archimedean copula-based <...

IN - Informatika

  • 2015
  • C
  • Link
Result

Bayesian methods in neural networks for inverse atmospheric modelling

is a Bayesian neural network pretrained to mimic a lognormal process and second one are modeled by a convolutional neural network. Both these approaches allow to incorporate......

Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

  • 2024
  • O
Result

A Comparison of Neural Networks and Bayesian MCMC for the Heston Model Estimation (Forget Statistics - Machine Learning is Sufficient!)

Main topics of the document: Heston model; parameter estimation; neural networks; MCMC...

Finance

  • 2023
  • O
  • Link
Result

Multi-objective Bayesian Optimization for Neural Architecture Search

for the Neural Architecture Search (NAS) in this paper. The method based on Bayesian allows to accompany the search for the optimal network by additional criteria besides the network performance. The NAS method is...

Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

  • 2023
  • D
  • Link
Result

Bayesian SZNet: Bayesian deep learning to predict redshift with uncertainty

Bayesian SZNet predicts spectroscopic redshift through use of a Bayesian convolutional network. It uses Monte Carlo dropout to associate predictions with predictive uncertainties, allowing the user to determine unusual or p...

Astronomy (including astrophysics,space science)

  • 2022
  • R
  • Link
Result

Recurrent Neural Network Based Boolean Factor Analysis and its Application to Word Clustering

Neural network based algorithm for word clustering as an extension of the neural network based Boolean factor analysis algorithm is introduced. Technique based on a Bayesian procedure has been developed to...

BB - Aplikovaná statistika, operační výzkum

  • 2009
  • Jx
Result

Identification of nonlinear non-gaussian systems by neural networks

Application of neural networks in identification of nonlinear non-Gaussian systems is treated. Stress is laid on a parameter estimation of the networks. They are trained by the Gaussian sum method which is a global filterin...

BC - Teorie a systémy řízení

  • 2005
  • D
Result

Usage of Data Mining Techniques on Marketing Research Data

This contribution contains problems of marketing research data classification by means of data mining algorithms. Three basic methods are described, classification with the aid of Multi-layer Perceptron neural network with Back-prop...

IN - Informatika

  • 2012
  • D
Result

Strictly modular probabilistic neural networks for pattern recognition.

Bayesian decision-making can be realized by a strictly modular probabilistic neural network. The autonomous adaptation of neurons includes only the locally available......

BB - Aplikovaná statistika, operační výzkum

  • 2003
  • Jx
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