Unconstrained optimization algorithms in python, line search and trust region methods

Implementation of approximate free-energy minimization in PyTorch

A Matlab/Octave package for oscillatory integration

Implementation of our paper entitiled FAMINet: Learning Real-time Semi-supervised Video Object Segmentation with Steepest Optimized Optical Flow published in TIM.

A matlab function for steepest descent optimization using Quasi Newton's method : BGFS & DFP

A Unified Pytorch Optimizer for Numerical Optimization

Implementation of unconstrained optimization techniques in Matlab

[NeurIPS2024 (Spotlight)] "Unified Gradient-Based Machine Unlearning with Remain Geometry Enhancement" by Zhehao Huang, Xinwen Cheng, JingHao Zheng, Haoran Wang, Zhengbao He, Tao Li, Xiaolin Huang

Fortran/Python linear algebra utilities

Demonstration of gradient descent methods

Implementations of various Algorithms used in Numerical Analysis, from root-finding up to gradient descent and numerically solving PDEs.

This repository consists of Lab Assignments for course Machine Learning.

Implementation of Unconstrained minimization algorithms. These are listed below:

This contains three programs written in python. Gauss-Seidel and Successive Over Relaxation to solve system of equations and Steepest-Descent to minimize a function of 2 or 3 variables.

Pseudo-Inverse, Gradient-Stochastic-Steepest Descent, Logistic Regression and LDA-QDA

Contains a mathematical optimization project implemented in Python

Numerical optimization algorithms with examples in Python.

The implementation of advanced mathematical optimization methods

Example Code for numerical optimization. Written in python.