Computational Methods for Optimization
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Updated
May 28, 2017 - MATLAB
Computational Methods for Optimization
Numerical Optimization Methods coursework | Institute for Applied System Analysis (2017)
Forecasting for AirQuality UCI dataset with Conjugate Gradient Artificial Neural Network based on Feature Selection L1 Regularized and Genetic Algorithm for Parameter Optimization
Reports of the assignments: Decision Models a.y. 2018/2019
Conjugate Gradient method (CG)
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.
MATLAB implementations of a variety of nonlinear programming algorithms.
Topology optimization code utilizing a Multi-Grid Conjugate Gradient solver.
Reimplementation of optimization algorithms.
(Nonlinear) optimization algorithms in C#
Implementation and visualization (some demos) of search and optimization algorithms.
Implementation of nonlinear Optimization Algorithms in Python
Identical directions generated by Linear Conjugate Gradient and David-Fletcher-Powell
Optimization in ML
Implementation of optimization algorithms in python
Gradient Descent (GD) v.s. Conjugate Gradient Descent (CGD) for 2-D Linear Regression
numerical optimization subroutines in Fortran generated by ChatGPT-4
Python Implementation and Visualization of Numerical Optimization Techniques
Density Functional Theory with plane waves basis, applied on a 'quantum dot'. Volumetric visualization of orbitals with VTK
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