Portfolio optimisation library.
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Updated
Jun 10, 2024 - Julia
Julia is a high-level dynamic programming language designed to address the needs of high-performance numerical analysis and computational science. It provides a sophisticated compiler, distributed parallel execution, numerical accuracy, and an extensive mathematical function library.
Portfolio optimisation library.
Variational approximation by Gridap package to resolve T.I.S.E. in Julia
Chemical reaction network and systems biology interface for scientific machine learning (SciML). High performance, GPU-parallelized, and O(1) solvers in open source software.
A comprehensive open source computer algebra system for computations in algebra, geometry, and number theory.
Automatic Finite Difference PDE solving with Julia SciML
High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)
PotentialLearning.jl: Developing Optimization Workflows for Fast and Accurate Interatomic Potentials.
A toolbox of simple solutions for common data cleaning problems.
Julia implementation for various Frank-Wolfe and Conditional Gradient variants
CoCalc: Collaborative Calculation in the Cloud
The Julia Programming Language
Simulation model of the biomass of grassland plant species
Library for the numerical simulation of closed as well as open quantum systems.
Quantum Toolbox in Julia
Finite element toolbox for Julia
Created by Jeff Bezanson, Stefan Karpinski, Viral B. Shah, Alan Edelman
Released February 14, 2012