Reservoir computing utilities for scientific machine learning (SciML)

Branch-and-Price-and-Cut in Julia

LowRankModels.jl is a julia package for modeling and fitting generalized low rank models.

Computing reachable states of dynamical systems in Julia

Tools for the exploration of chaos and nonlinear dynamics

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

A Julia package for solving systems of polynomials via homotopy continuation.

A package for binary and continuous, single and multi-material, truss and continuum, 2D and 3D topology optimization on unstructured meshes using automatic differentiation in Julia.

A JuMP-based Nonlinear Integer Program Solver

Clarabel.jl: Interior-point solver for convex conic optimisation problems in Julia.

Polyhedral Computation Interface

Implementations of the models from the Statistical Rethinking book with Turing.jl

Causal, Higher-Order, Probabilistic Programming

Automatic Finite Difference PDE solving with Julia SciML

A Julia package for statistical inference, data manipulation and visualization of phylogenetic networks

Interior-point solver in pure Julia

A Julia interface to the Ipopt nonlinear solver

Differentiable collision detection for polytopes, capsules, cylinders, cones, spheres, and polygons.

A Platform for Scalable Modeling and Optimization

A development environment for robust and global optimization

A Julia/JuMP Package for Unbalanced Power Network Optimization

Interior point solver for general convex conic optimization problems

Convenience meta-package to load essential packages for statistics

ConstraintSolver in Julia: Blog posts ->

Predictive Uncertainty Quantification through Conformal Prediction for Machine Learning models trained in MLJ.

A Julia interface to the CPLEX solver

System Identification toolbox, compatible with ControlSystems.jl

A solver for mixed-integer convex optimization

Proximal operators for nonsmooth optimization in Julia

Algorithms and data structures for game theory in Julia

Universal modeling and simulation of fluid mechanics upon machine learning. From the Boltzmann equation, heading towards multiscale and multiphysics flows.

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

A Julia implementation of basic tools for time series analysis compatible with incomplete data.

Extension functionality which uses Stan.jl, DynamicHMC.jl, and Turing.jl to estimate the parameters to differential equations and perform Bayesian probabilistic scientific machine learning

Probabilistic Numerical Differential Equation solvers via Bayesian filtering and smoothing

SymbolicNumericIntegration.jl: Symbolic-Numerics for Solving Integrals

Climate science package for Julia

Sum of Squares Programming for Julia

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

Combinatorial optimization layers for machine learning pipelines