Open-source implementation of AlphaEvolve

OpenAlpha_Evolve is an open-source Python framework inspired by the groundbreaking research on autonomous coding agents like DeepMind's AlphaEvolve.

LoongFlow is an expert-grade Agent framework for Loop Engineering. Through a Plan-Execute-Summary loop and structured experiential memory, it enables AI to continuously think, execute, reflect, and evolve across complex software engineering, mathematical, and machine learning tasks.

Iterative algorithms for solving linear systems, eigensystems, and singular value problems

BART: Toolbox for Computational Magnetic Resonance Imaging

Analyze Data with Pandas-based Networks. Documentation:

A curated list of papers and selected technical blogs on Loop Models.

Julia code for the book Numerical Linear Algebra

Algebraic Multigrid in Julia

This is a Julia package of nonlinear solvers. These codes are used in my book, Solving Nonlinear Equations with Iterative Methods: Solvers and Examples in Julia.

A fast forward- and inverse kinematics solver for Arduino based on the FABRIK algorithm. The solver supports up to 4 DOF.

Numerical computation in native Haskell

This algorithm uses a rectangle made by the user to identify the foreground item. Then, the user can edit to add or remove objects to the foreground. Then, it removes the background and makes it transparent.

pySDC is a Python implementation of the spectral deferred correction (SDC) approach and its flavors, esp. the multilevel extension MLSDC and PFASST.

An iterative machine learning framework for predicting temperature profiles for an additive manufacturing process

Code for our work on pose-estimation using template 3D models.

This repository mirrors the principal Gitlab repository of the Chebyshev Accelerated Subspace iteration Eigensolver. If you want to contribute as developer to this project please contact e.di.napoli@fz-juelich.de.

High-performance Krylov subspace and preconditioned iterative solvers for dense and sparse linear systems

General phase regularized MRI reconstruction using phase cycling

LSQR is an iterative method for solving large, sparse, linear systems of equations and linear least-squares problems, including under- or over-determined and rank-deficient systems. It uses the Lanczos bidiagonalization process to provide a robust alternative to conjugate gradients, offering better numerical stability. Solver