High accuracy derivatives, estimated via numerical finite differences (formerly FDM.jl)

Robust robotic localization and mapping, together with NavAbility(TM). Reach out to info@wherewhen.ai for help.

Reverse-mode automatic differentiation in Julia

Differentiating convex optimization programs w.r.t. program parameters

Fast inference for Gaussian processes in problems involving time. Partly built on results from https://proceedings.mlr.press/v161/tebbutt21a.html

Starter kit for legendary models

Build flexible hierarchical multi-instance learning models.

Clique recycling non-Gaussian (multi-modal) factor graph solver; also see Caesar.jl.

Robot Motion Estimate: Tools, Variables, and Factors for SLAM in robotics; also see Caesar.jl.

Nonlinear optical pulse propagator

Utilities for testing custom AD primitives.

Functionality for working efficiently with block diagonal matrices.

Machine learning with Mill.jl for JSON documents

Renamed to Avalon.jl

Structure Preserving Machine Learning Models in Julia

Fast approximate high-dimensional hierarchical Bayesian inference

A turbulence-convection single column model cloud parameterization.

Uncertainty Quantification in Julia

Distances to sets for MathOptInterface

Mixed-Integer Convex Programming: Branch-and-bound with Frank-Wolfe-based convex relaxations

🎲 Parameter estimation for Oceananigans using EnsembleKalmanProcesses

A package to calibrate atmospheric turbulence and convection parameterizations using gradient-free ensemble Kalman methods

Design scalable noise characterisation experiments for quantum computers

Model the propagation of VLF radio waves in the Earth-ionosphere waveguide.

Better Radial velocities from Stellar Spectroscopy via Machine Learning

Operator layers for Flux.jl that allow for the construction of Neural Operator models by using Flux's API. Useful for discretization-independent spatio-temporal ML models.

Matlab's language functions written in Julia

Romberg integration routine in Julia

Allow to use BifurcationKit.jl with Gridap.jl

Collection 3D visualization tools associated with the Caesar.jl and RoME.jl robot navigation packages

A semidefinite programming solver for clustered low-rank SDPs

Julia Implementation of the nonintrusive model reduction approaches: Operator Inference (OpInf) and Lift & Learn (LnL)

Generalized Estimating Equations (GEE) in Julia

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

Variable Selection with Knockoffs

High performance hybrid Monte Carlo simulation

Reliability-based optimization

Data-driven models for extremely precise radial velocity (EPRV) spectra

Optimally tuned ridge regression when features can be partitioned into groups.

Permutation tests for MixedModels.jl