A user-friendly Bayesian software to analyse mixed models
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Updated
Mar 2, 2023 - R
A user-friendly Bayesian software to analyse mixed models
An implementation of adPredictor in Java and MapReduce
MCMC Generalized linear model ; Normal Priors
A study on deep learning methods to identify precise boundaries for robot navigation
Functional Spatial Temporal Aggregated Dirichlet Process Predictors
CSCI5822 Probabilistic Models in Machine Learning final project [Spring 2021].
Tools for the Bayesian Discount Prior Function
Supporting data and code for manuscript titled 'Modelling the persistence and control of Rift Valley fever virus in a spatially heterogeneous landscape'.
Selected examples of Bayesian inference using MCMC sampler algorithms.
Artificial Intelligence system that generates a crossword puzzle, and also solves it, given a structure and dictionary of words.
Bayesian multinomial logistic regression implemented in R with runjags for MCMC.
Here you can find several cpp projects i've done while im learning this programming language.
A package for Bayesian meta-analytic SEM
Probabilistic bayesian modelling for critical decisions in complex systems.
BayesianSampler is a simple, extensible module for understanding Bayesian Network, Joint Probability and Sampling process. It built on top of Numpy and Pandas to provide an intuitive and working numbers so student can learn better about probabilistic model.
Scripts used in the publication "Continent-wide recent emergence of a global pathogen in African amphibians" by Ghose et al. (2023)
Machine Learning Algorithm Implementation and Projects
Gaussian Processes for Global Optimization: efficient optimization of expensive-to-evaluate functions
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