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.

Gemini API wrapper for Julia

Generalized Gaussian Quadrature Rules

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A thin wrapper around the python PyMBAR

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Wrapper to python module for reading and writing 3D data

Implement mullerlab/generalized-phase in Julia

Julia wrapper for the Python Rhodium package

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Julia package for recovering stratified spaces underlying point clouds.

Multi-trajectory and local search methods in Nonconvex.jl

Julia bindings for Tinkerforge devices based on wrapping the Python bindings.

Sparse sensor placement in Julia

Reader and writer for JSON metabolic models

Implement gray and colored 2d and 3d histograms of images.

Package for generation of Julia gene regulatory network models

Percival wrapper in Nonconvex.jl

[WIP] Core types and functions for QED.jl

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Explores representations based on bag words

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Pavito wrapper in Nonconvex.jl

Wrapper of NOMAD.jl using the Nonconvex.jl API.

Dithering Algorithms for Julia

NLopt wrapper in Nonconvex.jl.

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Colocalization metrics and distances for images or their sparse representations.

Implementation of the spectral energy distribution QSOSED for active galactic nuclei.

Multi-start optimization in Nonconvex.jl

A Julia package for multiple kernel learning based one-class support vector machine.

Juniper wrapper in Nonconvex.jl

Generate Julia code for cli programs using a variant of Fig specifications.

Ipopt wrapper for Nonconvex.jl.

Gaussian process models for spatial transcriptomics

Constrained Bayesian optimization implementation in Nonconvex.jl