Package to parse Basis Sets from Basis Set Exchange API

Microscope Point Spread Function Calculator

Variable Selection with Knockoffs

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Extra non essential functionality for MixedModels.jl

A Julia package for computing a (fine) mixed subdivision and the mixed volume of lattice polytopes

Digital signal processing for radiation detectors

A toolkit for the quantum and classical Dicke model in Julia.

Julia library and command-line tools implementing the RainFARM stochastic precipitation downscaling method.

Symmetry-allowed k ⋅ p expansions

Provides a general framework for implementing and performing Kernel Density Estimation

Dealing with ERA5 Reanalysis datasets

Modular framework for cut pruning algorithms

Counterfactual Regret Minimization Game solution methods for Julia

Julia package for easy access to and efficient broadcasting over properties

An interface for solving a stochastic capacity expansion problem via a Dantzig-Wolfe decomposition algorithm

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

Anytime error minimization search for POMDPs, implemented in Julia.

Geometry optimization for molecular simulation

Solver for complemetarity-based dynamics.

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

High performance hybrid Monte Carlo simulation

Use PETSc solvers in sequential and parallel Julia runs

Extension of `Graphs.jl` to graphs with named vertices.

Implementation of DDA and CEMD method in julia

A custom branch-and-bound algorithm for solving low-rank matrix completion to certifiable optimality

Julia package for MPI reconstruction

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Optimization of Energy Communities in Julia

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Recursive causal discovery with Julia

Plot critical difference diagrams in Julia

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

Point-based value iteration solver for POMDPs

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

A collection of structures to define observation or action spaces of Reinforcement Learning environments. [May be moved into CommonRLInterface once stable]

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

Conversions between Distributions.jl distributions and MeasureTheory.jl measures.

Julia implementation of Factored Spectrally Transformed Linear Mixed Models