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
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
Java and Processing implementations for visualising various MCMC methods.
Better implementation of vangj's viz library - Simple Bayesian Belief Network visualization and interactive library for JavaScript.
Barzen JA, SJ Converse, PH Adler, A Lacy, E Gray, and A Gossens. 2018. Examination of multiple working hypotheses to address reproductive failure in reintroduced Whooping Cranes. The Condor 120:632-649
Using Linear and Quadratic discriminant analysis, KNN and Naive Bayes to develop a tool that can classify wines into one of the three types based on the other variables provided.
This package contains a template for following the Bayesian workflow, complete with examples.
Repo has python code for implementation of various machine learning classifier and assignment for EED363 at Shivnadar University
An implementation of the Metropolis algorithm.
A julia package to compute Gittins Indices for Multi Armed Bandits
Java Implemention of Data Warehousing and Mining algorithms
This work is the preliminary experiments leading to the publication: Towards Invariant Soft Biometrics from Electrocardiograms
Bayesian Multi-Parameter Evidence Synthesis (MPES) to estimate TB epidemiological parameters.
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