Implementation of approximate free-energy minimization in PyTorch

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

A Matlab/Octave package for oscillatory integration

[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

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

Fortran/Python linear algebra utilities

Implementation of unconstrained optimization techniques in Matlab

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

Numerical optimization algorithms with examples in Python.

Demonstration of gradient descent methods

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.

Implementation of Unconstrained minimization algorithms. These are listed below:

This repository consists of Lab Assignments for course Machine Learning.

📉🏞️ Steepest Descent Algorithm for Water Molecules Energy Minimization 🔍🌊

Assignments for Optimization Techniques Course at ECE AUTH. Includes Steepest Descent, Levenberg-Marquardt and a Genetic Algorithm implementation for Network Traffic Optimization.

Python implementations of classical nonlinear optimization methods, including Newton, steepest descent, conjugate gradient, and Armijo line search.

Comparison of Steepest Descent and Conjugate Gradient iterative solvers for SPD linear systems with experimental analysis and LaTeX paper

Through this project we will try to understand working of Steepest-Descent and Gradient-Descent method and the differences between them