Gaussian KDEs in Julia.

A light-weight GaussianProcesses.jl wrapper

Plots regularization paths generated by Lasso.jl

-

Compute MLEs for linear covariance models

Marginalized log-probability functions in Julia

Like fireflies next to spotlights

-

Fast informed bound solver for POMDPs.

Library for storing your MCMCChains without serialization.

A package for performing Metropolis Hasting Algorithm.

Fast construction of Gaussian Process Regression models supporting gradient information.

A collection of extended Generalized Pareto distributions (EGPD) and related functions.

This packege made foe bioequivalence testing.

Agent-based modeling of microbial motile behavior via Agents.jl

Microbot tracking and analysis with Julia.

-

Simulation of eco-evolutionary dynamics on multi-trait networks

A staging ground for serialization in the MixedModels ecosystem

A simple interface for defining, training, and deploying MDNs.

More algorithms for the Erdos.jl graph library

-

A user-friendly tool to solve linear equations and nonlinear equations.

-

Julia package for sampling and generating points on the boundary of an ellipse with methods for random, equally spaced and clustered points

-

Julia package for simulating multifractal random fields according to Gaussian multiplicative chaos theory.

Interpolation of functions using Chebyshev polynomials

-

Earth (multivariate adaptive regression splines) for Julia

Differentiable neural network with easy access to Jacobians of the output wrt the input and the network parameters.

Access NavAbility cloud factor graph features from Julia alongside Caesar.jl and others

Julia package for working with Dynamic Linear Models.

Abstraction Layer for Dynamic Bounds

Bounds and Relaxations of Parametric Differential Equations

Traits for specifying the orientation of features and observations in data

Easy way to use public outlier detection datasets with Julia

Test Toolkit for Outlier Detection Algorithms

Stan only version of DiffEqBayes.jl

Provides core functionality of DerivableFunctions.jl without loading backends.