WAIC and PSIS model comparison methods as explained in Statistical Rethinking.

A package for obtaining the effective time-averaged Lindbladian.

Distributions for continuous variables

Finite Element tools in Julia: Nonlinear deformation application

Full field solutions of Poisson and Stokes problems in 1D, 2D and 3D. Full field solutions to other problems are welcome!

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Simulate EEG / ERP data with overlap, non-linear effects, multiple regression

DNA Motif discovery that includes the discovery of flexible (long or gapped) motifs.

Neural-Network Outlier Detection Algorithms for Julia

A package for representing orthogonal polynomials as quasi arrays

Just the Comrade Models

An implementation of the cross entropy method that works well for time series

Tools for solving constrained dynamical systems

Julia implementation of the original R sensemakr package: https://github.com/carloscinelli/sensemakr

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A lightweight Consensus-Based Optimisation package for Julia

A Package for Estimating Stochastic Frontier Models using Julia

NeuralFieldEq.jl: An efficient solver to compute Neural Field Equations in several scenarios

Library for simulating time binned photons in Waveguide Quantum Electrodynamics

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.

Differentiable wrapper for FrankWolfe.jl convex optimization routines

Julia package for producing jammed configurations of hard-spheres using iterative linear programming.

Alignment and comparison of small molecules read from .sdf files represented as Gaussian Mixture Models.

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

Algorithms for performing angular differential imaging (ADI)

Compute Bell inequalities and their quantum violations.

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

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Causal Inference using Gaussian Processes with Structured Latent Confounders. Estimate treatment effects with Gaussian processes.

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

Geometry optimization for molecular simulation

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

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

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Http://proceedings.mlr.press/v119/bruinsma20a.html

Sampling quantum phase space distributions

Method to estimate phylogenetic networks from algebraic invariants

Power spectra on the masked sky

Quantum Exact Simulation Toolkit is a high performance simulator of quantum circuits, state-vectors and density matrices

Julia stochastic processes package.