A Monte-Carlo implementation in the julia language

The Julia Implementation of Gradient Boosting.

Distributed matrix-free linear algebra. Part of the COFII framework.

Image files for olive

Initial conditions of astrophysical simulations

Julia OpenPolicyAgent Client, Server and CLI.

Transliterate Beta Code Greek to Unicode Greek

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Adaptive persistency-based mechanism for Dispatcher task graphs

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Gaussian Mixture Model Parameter Estimation

A few functions for working with indefinite quadratic forms.

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A collection of global matching models of recognition memory

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Gaussian Processes for MLJ

GPU-accelerated algorithms for flux sampling in CUDA.jl

Discriminative Circuits from the Juice library

Cim-optimizer wrapper for JuMP

A package for generating and analyzing Aztec diamonds

Utility package to connect to databases in the OMOP CDM format

Common calculations within orbital mechanics and astrodynamics.

Collection of Collaborative Datasets for Persa.jl

A Julia package generated using the OpenAPI Generator, providing a convenient API client for interacting with Mattermost chat platforms, supporting various operations and data models with seamless integration.

Read and use GEOTRACES data in Julia.

A Julia package for statistical modeling of binned data, e.g. histograms.

Models of control pods of remote controlled kites

An opensource implementation of several kernel methods

An adapter package that implements Lighthouse's framework interface for Flux

Solvers for autonomous matrix-valued generalized differential Riccati equations (GDREs) with low-rank solutions.

Methods for the evaluation of maximum entropy distributions

Multi-dimensional labeled sparse arrays

ASDF, the Advanced Scientific Data Format

Estimate LoD from data

Plots.jl recipes for the GeoStats.jl framework

Efficiently compute gradients of g(x,p) where A(p)x=b(p)

A julia package implementing the kanones system for building Greek morphological parsers.

Efficient optimal selection for tree breeding

Estimation of Shannon Entropy for Discrete Random Variables