MATLAB implementations of a variety of nonlinear programming algorithms.
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Nov 13, 2020 - MATLAB
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MATLAB implementations of a variety of nonlinear programming algorithms.
numerical optimization in pytorch
C++ implementation for Bundle Adjustment in 2-View
JuliaGrid is an easy-to-use power system simulation tool for researchers and educators provided as a Julia package.
Implementation of Lucas Kanade Tracking system using six parameter affine model and recursive Gauss-Newton process.
C++ implementation of Lucas-Kanade-Image-Alignment
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
2D bearing-only SLAM with least squares
Second order optimization with automatic differentiation
collection of numerical optimization methods
An efficient and easy-to-use Theano implementation of the stochastic Gauss-Newton method for training deep neural networks.
Redbird - A Model-Based Diffuse Optical Imaging Toolbox
Different type of solvers to solve systems of nonlinear equations
Stochastic Second-Order Methods in JAX
[Optimization Algorithms] Implementation of Nonlinear least square curve fitting using the Gauss-Newton method and Armijio’s line search.
A C++ library for solving nonlinear least squares problems using Gradient Descent, Gauss-Newton and Levenberg-Marquardt solvers
Code to conduct experiments for the paper Regularization and acceleration of Gauss-Newton method.
Code related to Optimization Techniques
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