Package for modeling glycolysis activity

Point-based value iteration solver for POMDPs

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Bayesian addition to Flux.jl

Package to map SPH particle data to a cartesian grid

Repository for plotting implicitly defined surfaces and curves in R3.

Highly flexible and efficient computation of n-dimensional binned statistic(s) for n-variable(s)

Power spectra on the masked sky

A companion package for Microbiome.jl for working with the Biobakery family of computational tools

BioCCP.jl exploits the Coupon Collector Problem for sample size determination in combinatorial biotechnology.

Fast implementations of FastICA and DUET for blind source separation

Independent Hypothesis Weighting for multiple testing with side-information in Julia

Geometry optimization for molecular simulation

Tools to specify and simulate individual based models, using applied category theory

A Julia based implementation of Plug and Play Language Models

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BitArray representation of genetic sequences in Julia

A Julia package for piecewise spectral methods such as p-FEM

Julia Implementation of Integral Arrays

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Fast (multivariate) rejection sampling of PDFs using interpolation approximation.

Strategy simulation for simple games.

Julia package for football analytics

A Julia package for computing singular integrals

Definitions of the Julia types for simulating an ISO's market clearing.

Method to estimate phylogenetic networks from algebraic invariants

Nonlinear diffusion problems in Julia

Implements a generic Inverted Index data structure for full text search and other kinds of search domains

Sampling quantum phase space distributions

Use PETSc solvers in sequential and parallel Julia runs

A Makie theme

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

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A thin wrapper over Bridge.jl for the SciML scientific machine learning common interface, enabling new methods for neural stochastic differential equations (neural SDEs)

Simple linear and nonlinear solvers in Julia

Jet operator pack for seismic modeling dependent on WaveFD.jl. Part of the COFII framework.

Julia implementation of Autocorrelation Wavelets.

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

Hypothesis tests of calibration.

Many-body objects for quantum computing: a Julia implementation