Implementation of approximate free-energy minimization in PyTorch
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Updated
Oct 16, 2021 - Python
Implementation of approximate free-energy minimization in PyTorch
Implementation of our paper entitiled FAMINet: Learning Real-time Semi-supervised Video Object Segmentation with Steepest Optimized Optical Flow published in TIM.
A Unified Pytorch Optimizer for Numerical Optimization
[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 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.
Contains a mathematical optimization project implemented in Python
Example Code for numerical optimization. Written in python.
Through this project we will try to understand working of Steepest-Descent and Gradient-Descent method and the differences between them
Course assignments for CL 663: IIT Bombay
Through this project we will try to understand working of Steepest-Descent and Gradient-Descent method and the differences between them.
This repo contain implementation of Steepest Descent algorithm using inexact line search and Newton's method on Functions like Tried Function, Three Hump Camel, Styblinski-Tang Function, Rosenbrock Function, etc.
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