MATLAB implementations of a variety of nonlinear programming algorithms.
-
Updated
Nov 13, 2020 - MATLAB
MATLAB implementations of a variety of nonlinear programming algorithms.
Implementation and visualization (some demos) of search and optimization algorithms.
Density Functional Theory with plane waves basis, applied on a 'quantum dot'. Volumetric visualization of orbitals with VTK
Conjugate Gradient method (CG)
Optimization in ML
(Nonlinear) optimization algorithms in C#
Implementation of nonlinear Optimization Algorithms in Python
numerical optimization subroutines in Fortran generated by ChatGPT-4
Topology optimization code utilizing a Multi-Grid Conjugate Gradient solver.
Forecasting for AirQuality UCI dataset with Conjugate Gradient Artificial Neural Network based on Feature Selection L1 Regularized and Genetic Algorithm for Parameter Optimization
CG is a FORTRAN77 library by Sourangshu Ghosh which implements a simple version of the conjugate gradient (CG) method for solving a system of linear equations of the form A*x=b, suitable for situations in which the matrix A is positive definite (only real, positive eigenvalues) and symmetric.
Monte Carlo based method for Radioactive Particle Tracking technique based on Qt C++/C++
Gradient Descent (GD) v.s. Conjugate Gradient Descent (CGD) for 2-D Linear Regression
Numerical Optimization Methods coursework | Institute for Applied System Analysis (2017)
Reimplementation of optimization algorithms.
Computational Methods for Optimization
Implementation of optimization algorithms in python
Reports of the assignments: Decision Models a.y. 2018/2019
Identical directions generated by Linear Conjugate Gradient and David-Fletcher-Powell
Python Implementation and Visualization of Numerical Optimization Techniques
Add a description, image, and links to the conjugate-gradient-descent topic page so that developers can more easily learn about it.
To associate your repository with the conjugate-gradient-descent topic, visit your repo's landing page and select "manage topics."