Standard environments for benchmarking the performance of RL algorithms.

EPMA matrix correction algorithms

A lightweight Julia package for modeling and solving Newsvendor Problems.

Base package that ships symbols and functionality that is relevant to all or multiple packages in the ecosystem

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Adds support for parallelization for Taija packages.

Standard data cleaning tools prior to generating BEAST xml file

A Julia package for inverting Taylor series

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Tensor decomposition algorithms

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BaytesSMC.jl is a library to perform SMC proposal steps on `ModelWrapper` structs, see ModelWrappers.jl. Kernels that are defined in BaytesMCMC.jl and BaytesFilters.jl can be used inside this library.

A library to perform particle MCMC proposal steps for parameter in a `ModelWrapper` struct, see [ModelWrappers.jl](https://github.com/paschermayr/ModelWrappers.jl).

Optimization library for Baytes modules

A library to perform MCMC proposal steps on `ModelWrapper` structs, see ModelWrappers.jl.

A library to perform particle filtering for one parameter in a `ModelWrapper` struct.

Wrappers to differentiate `ModelWrapper` structs, see ModelWrappers.jl.

Bayesian regression models for size-and-shape data

Using a population of profiles to approximate the real motifs

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Julia simulation package for TKTD models

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Test cases for BAT.jl and for Bayesian Julia software in general

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This is a dimensionality reduction algorithm which has the goal of maintaining interpretability i.e we eliminate variables directly from potential models that don't seem to add any predictive power.

Weibull Distribution allowing a Pareto approximation.