MATLAB implementations of a variety of nonlinear programming algorithms.

numerical optimization in pytorch

JuliaGrid is an easy-to-use power system simulation tool for researchers and educators provided as a Julia package.

C++ implementation for Bundle Adjustment in 2-View

C++ implementation of Lucas-Kanade-Image-Alignment

Implementation of Lucas Kanade Tracking system using six parameter affine model and recursive Gauss-Newton process.

MATGRID is an easy-to-use power system simulation tool for researchers and educators provided as a MATLAB package.

Developed and implemented 2D and 3D Pose Graph SLAM using the GTSAM library and Gauss Newton Solver on the Intel and Parking Garage g2o datasets respectively

collection of numerical optimization methods

Code and data for the Robotics 2026 paper “Efficient Incremental SLAM via Information-Guided Gating and Selective Partial Optimization”; includes MATLAB/Octave reference code plus C++ and Python prototypes.

2D bearing-only SLAM with least squares

Second order optimization with automatic differentiation

Second-Order Methods in JAX

Redbird - A Model-Based Diffuse Optical Imaging Toolbox

An efficient and easy-to-use Theano implementation of the stochastic Gauss-Newton method for training deep neural networks.

A C++ library for solving nonlinear least squares problems using Gradient Descent, Gauss-Newton and Levenberg-Marquardt solvers

Different type of solvers to solve systems of nonlinear equations

[Optimization Algorithms] Implementation of Nonlinear least square curve fitting using the Gauss-Newton method and Armijio’s line search.

This repository contains a collection of MATLAB scripts that implement some of the classical optimization methods for unconstrained optimization models: Steepest-Descent, Newton method, Gauss-Newton, Conjugate Gradient method, Fibonacci search, Golden-section search, Dichotomous search and Exhaustive search.