A Julia package for Differential Evolution MCMC

Modern Hopfield layer implementations in Julia

Package to build Cases for Power Systems Modeling

A differentiable parametrization of a group of unitary matrices.

Julia package with several functions to train and analyze Autoencoder-based neural networks

Is there anything we can't make Bayesian?

Implementation of Integral Probability Measures in Julia

EHT Image domain analysis through template matching.

Julia implementation of elliptical slice sampling.

Thermodynamic Integration for Turing models and more

Adaptive stress testing of black-box systems within POMDPs.jl

Experimental features for Flux.jl

Symbolic modeling in Julia!

Scrape EDGAR filings from https://www.sec.gov/

Building and using pyramids for large raster data

Collection of layers that can perform arithmetic operations

Sklearn Interface and Distributed Training for Flux.jl

A set of tools to solve potential flows past bodies on a Cartesian grid

Graph-building for AtomicGraphNets

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Julia implementation of Modal Decision Trees & Forests, for interpretable classification of spatial and temporal data. Long live Symbolic Learning!!

Manage unstructured and multimodal datasets!

Lightweight module of neural differential equations in Kinetic.jl

A high-performance library for gradient based quantum optimal control

A simple library for handling NMR data in Julia

A Julia package for behavioural modeling

Static site generation with Pluto, WIP

JutulDarcyRules: ChainRules extension to Jutul and JutulDarcy

Istope-enabled implementation of the LWF-BROOK90 hydrological model in Julia

Implementation of Arxiv:2212.08549 in Julia

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Linear models

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'Pareto optimal' package recommendations for your current dependencies.

Differentiable 2d rasterizer in Julia

Operator layers for Flux.jl that allow for the construction of Neural Operator models by using Flux's API. Useful for discretization-independent spatio-temporal ML models.

Optimal experimental design of ODE and DAE systems in julia

A Julia package for parameterized convex approximators including parameterized log-sum-exp (PLSE) network.

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Tools for solving partial differential equations by immersing surfaces and their operations in Cartesian grids