Backend for Lux.jl

ConceptualClimateModels.jl is a Julia package for creating and analysing conceptual models of climate, such as energy balance models, glaciation cycle models, or climate tipping models.

(Hierarchical) Phylogenetic Models in Julia

A lightweight Consensus-Based Optimisation package for Julia

Tools for solving constrained dynamical systems

Julia package for Determinantal Point Processes

Implementation of a GNSSReceiver

Parsers and processing for geoenergy data file formats in Julia.

A Julia package for real-time audification of ODEs and SDEs

A package for obtaining the effective time-averaged Lindbladian.

A collection of functions to analyze phonetic data

Fast, minimal histogram algorithms.

For analysis and plotting of your isotopic ratios. In the spirit of (but not derived from) IsoplotR and the original Isoplot

Finite Element tools in Julia: Nonlinear deformation application

Finite Element tools in Julia: Heat diffusion application

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An Open Nonlinear Structural Analysis Solver in Julia

Package for fitting models according to the deep compartment modeling framework for pharmacometric applications.

Fast Dispersion Measure Transform implemented in Julia

Julia package for MPI reconstruction

A julia repository aimed a providing efficient geographic projections for production scale workflows

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A Makie theme

Microscope Point Spread Function Calculator

Numerical Methods for Vlasov-Poisson and Vlasov-Maxwell Systems

A Julia implementation of estimation and validation algorithms for time series compatible with incomplete data.

Save videos from Julia

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Plot critical difference diagrams in Julia

Https://stevengogogo.github.io/FindSteadyStates.jl/dev

Image registration using mutual information.

Solver for complemetarity-based dynamics.

Nonlinear diffusion problems in Julia

This is a Julia library for processing ESA Sentinel 2 satellite data.

Experimental Approach to McCormick Relaxation Source-Code Transformation

Perform image hashing in julia

Variable Selection with Knockoffs

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Unfortunately, FMUs (fmi-standard.org) are not differentiable by design. To enable their full potential inside Julia, FMISensitivity.jl makes FMUs fully differentiable, regarding to: states and derivatives | inputs, outputs and other observable variables | parameters | event indicators | explicit time | state change sensitivity by event

A Julia package for modelling Algorithmic Recourse Dynamics.