DFT from SDR directly in a Julia REPL !

CDCL SAT Solver

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This is an visualization package.

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Summarize a DataFrame, as might be needed for a manuscript's *Table 1*

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

Adds support for parallelization for Taija packages.

Moose inspired finite elements in julia

A box-picking POMDP created using POMDPs.jl

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Julia package to perform a "temperate" OPF that avoid saturated lines in power systems

Adds plotting capabilities to BoltzmannMachines.jl

Ten Puzzle Solver in Julia.

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A prototype of a reactive Webapp for bitemporal data management of insurance contracts.

Simple biological particle simulation system.

[DEPRECATED] I deleted this repo a while ago. Forked backup from https://github.com/UnofficialJuliaMirror/Bioinformatics.jl-c429c406-9079-5a14-8339-dedc8835de90.

A Julia package for simulation, verification and parameter estimation of Biochemical Networks with Approximate Bayesian Computation (ABC) methods.

Graphical interface for BiochemicalAlgorithms.jl

General interface for flux-based constrained metabolic models

Hebrew orthography in Julia

Standard data cleaning tools prior to generating BEAST xml file

Non parametric productivity analysis under the B-disposal assumption

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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.

Optimization library for Baytes modules

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

A interior-point solver for semidefinite programming written in pure Julia.

Julia simulation package for TKTD models

Core structures that are shared for various Baytes modules

Bayesian regression models for size-and-shape data

Julia wrapper for the Tropical Polyhedra Library

Make Julia code probabilistic-programming-ready by allowing calls to `sample` to be annotated with traced addresses.

Trace estimation methods for matrix functions.

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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.