Rene Donner
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Medical Volume Annotator mva.ai
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Create LaTeX documents from within Julia, including image handling
Functional, efficient data manipulation framework
Declarative, per-project package management for Julia
Fast hierarchical medoid clustering
File watcher in Julia - can be used to auto-run unit tests etc
Utility functions for the FunctionalData package, mainly from the area of computer vision / machine learning
Repositories
117Fast hierarchical medoid clustering
Statistical shape models / point distribution models
zig-sqlite is a small wrapper around sqlite's C API, making it easier to use with Zig.
c-api for imgui (https://github.com/ocornut/imgui) Look at: https://github.com/cimgui for other widgets
Package to call the NLopt nonlinear-optimization library from the Julia language
Fast, low-memory method for batch and online clustering
Create LaTeX documents from within Julia, including image handling
Functional, efficient data manipulation framework
Declarative, per-project package management for Julia
Easier pre-compilation of code using userimg.jl (deprecated)
Example of using a precompiled sysimage in Julia 1.8
Code coverage tool for compiled programs, Python and Bash which uses debugging information to collect and report data without special compilation options
Implementation of Random Ferns classifier / regressor
Utility functions for the FunctionalData package, mainly from the area of computer vision / machine learning
Julia Binding to the GraphViz library
Koç University deep learning framework.
Julia module for reading/writing NIfTI MRI files
Interface to the Coin-OR Cbc solver for mixed-integer programming
DICOM for Julia
Julia package for libnettle
Talks and code for the Vienna Julia Meetups
Simple, consistent interfaces for any codec.
zlib codecs for TranscodingStreams.jl.
Convert between arrays of Dicts and DataFrames in Julia
Julia bindings to Vega-Lite
Matlab interface for calling Julia
File watcher in Julia - can be used to auto-run unit tests etc
Implementation of Differential Evolution with optional custom predictors
Basic statistics for Julia
Classification and Regression (also with n-D targets) using Extremely Randomized Trees