Julia wrappers for the PETSc library

Fast derivative evaluation

PortAudio wrapper for the Julia programming language, compatible with the JuliaAudio family of packages

State estimation, smoothing and parameter estimation using Kalman and particle filters.

Evaluating Robustness of Neural Networks with Mixed Integer Programming

Combinatorial optimization layers for machine learning pipelines

A package for time series data processing, classification, clustering, and prediction.

A standard library of components to model the world and beyond

Clifford circuits, graph states, and other quantum Stabilizer formalism tools.

Equation-based modeling and simulations in Julia

Koma is a Pulseq-compatible framework to efficiently simulate Magnetic Resonance Imaging (MRI) acquisitions. The main focus of this package is to simulate general scenarios that could arise in pulse sequence development.

Koma is a Pulseq-compatible framework to efficiently simulate Magnetic Resonance Imaging (MRI) acquisitions. The main focus of this package is to simulate general scenarios that could arise in pulse sequence development.

Toolbox for gradient-based and derivative-free non-convex constrained optimization with continuous and/or discrete variables.

A statistical toolbox for diffusion processes and stochastic differential equations. Named after the Brownian Bridge.

Tools for building non-allocating pre-cached functions in Julia, allowing for GC-free usage of automatic differentiation in complex codes

Statistical bootstrapping library for Julia

Julia package for the construction of quantum lattice systems.

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

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Using Vulkan from Julia

Utilities and abstractions for Machine Learning tasks

Access MySQL from Julia

Word cloud generator in julia

Starter kit for legendary models

Exploratory analysis of Bayesian models with Julia

An ODBC interface for the Julia programming language

Assorted basic Ordinary Differential Equation solvers for scientific machine learning (SciML). Deprecated: Use DifferentialEquations.jl instead.

Explainable AI in Julia.

Prediction of timeseries using methods of nonlinear dynamics and timeseries analysis

Probabilistic Circuits from the Juice library

Package for dynamical modeling of power grids

Optimization package for the Security-Constrained Unit Commitment Problem

Parallel distributed-memory version of Gridap

Transforms and pipelines with tabular data in Julia

Bilevel optimization in JuMP

Julia chess programming library.

Sparse, General Linear Algebra for Graphs!

A Julia interface to the HiGHS solver

Collection of fundamental physical constants with uncertainties. It supports arbitrary-precision constants

Utility package for generating, loading, splitting, and processing Machine Learning datasets