This demo nstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and model parameters as unknowns. The derivation and details are presented in: Christophe Andrieu, N ...
This demo nstrates the use of the reversible jump MCMC algorithm for neural networks. It uses a hierarchical full Bayesian model for neural networks. This model treats the model dimension (number of neurons), model parameters, regularisation parameters and noise parameters as random variables that n ...
monte carlo 仿真英文电子书
AGuidetoMonteCarloSimulationsinStatisticalPhysics,Second EditionThis new and updated deals with all aspects of Monte Carlo simulation ofcomplexphysicalsystemsencounteredincondensed-matterphysicsandsta-tistical mechanics as well as in related ?elds, for example polymer scie ...
This folder has some scritps that you may find usefull.
All of it comes from questions that I ve received in my email.
If you have a new request/question, feel free to send it to marceloperlin@gmail.com.
But please, don t ask me to do your homework.
Passing_your_param0
This folder contains inst ...
pMatlab is a toolsbox from MIT for running matlab in parallel style on a multi-core PC or a cluster environment. These two documents summary the usage of pMatlab and running time measurements on three simple Monte Carlo simulation codes.
Matlab is an ideal tool for simulating digital communications systems, thanks to
its easy scripting language and excellent data visualization capabilities. One of the
most frequent simulation tasks in the field of digital communications is bit-error-
rate testing of modems. The bit-error-rate perfor ...
Sequential Monte Carlo without Likelihoods
粒子滤波不用似然函数的情况下
本文摘要:Recent new methods in Bayesian simulation have provided ways of evaluating posterior distributions
in the presence of analytically or computationally intractable likelihood functions.
Despite representing a substantial ...
