Probabilistic Numerical Differential Equation solvers via Bayesian filtering and smoothing

A Julia package for the creation, manipulation and analysis of the structure, dynamics and functions of multilayer graphs.

Algebraic Multigrid in Julia

Perceptually Uniform Colour Maps for Julia

A package for Counterfactual Explanations and Algorithmic Recourse in Julia.

SymbolicNumericIntegration.jl: Symbolic-Numerics for Solving Integrals

Julia library for homological persistence

A bunch of helper functions for transferring data between worker processes

Large-scale, distributed, sparse linear algebra in Julia.

Climate science package for Julia

Hydrological modeling

Line search methods for optimization and root-finding

Julia implementation of Parquet columnar file format reader

Causal.jl - A modeling and simulation framework adopting causal modeling approach.

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

Julia wrappers for the PETSc library

Evaluating Robustness of Neural Networks with Mixed Integer Programming

Combinatorial optimization layers for machine learning pipelines

Equation-based modeling and simulations in Julia

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

A standard library of components to model the world and beyond

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

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

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.

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

Fast and automatic structural identifiability software for ODE systems

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Utilities and abstractions for Machine Learning tasks

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

An easy-to-use, modular, extendable and absurdly fast Julia package for dynamical billiards in two dimensions.

Exploratory analysis of Bayesian models with Julia

Explainable AI in Julia.

Starter kit for legendary models

Probabilistic Circuits from the Juice library

Optimization package for the Security-Constrained Unit Commitment Problem

Concurrent computing in Julia based on the Actor Model

Package for dynamical modeling of power grids

Parallel distributed-memory version of Gridap

Transforms and pipelines with tabular data in Julia