Newton and Quasi-Newton optimization with PyTorch
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Updated
May 29, 2025 - Python
Newton and Quasi-Newton optimization with PyTorch
Implementation and visualization (some demos) of search and optimization algorithms.
Hessian-based stochastic optimization in TensorFlow and keras
This package is dedicated to high-order optimization methods. All the methods can be used similarly to standard PyTorch optimizers.
A Unified Pytorch Optimizer for Numerical Optimization
Newton’s second-order optimization methods in python
Compilation of the assignments of the course of COL726: Numerical Algorithms (Spring 2021) and their solutions
Implementation of Unconstrained minimization algorithms. These are listed below:
Code for the AISTATS 2024 paper: "Krylov Cubic Regularized Newton: A Subspace Second-Order Method with Dimension-Free Convergence Rate".
simple code to solve algebraic equation and system of equations
In numerical analysis, Newton's method, also known as the Newton–Raphson method, named after Isaac Newton and Joseph Raphson, is a root-finding algorithm which produces successively better approximations to the roots (or zeroes) of a real-valued function.
Global Optmization with Gradients: Python implementation of an experimental non-local Newton method
Nonlinear optimization course's project is about iterative methods due to finding an optimal point for a function in Rn.
Este repositorio contiene los archivos que crean una interfaz gráfica para el simulador de un movimiento parabólico amortiguado.
Project II from CISC.820.01 - Quantitative Foundations
a Python implementation of various optimization methods for functions using Streamlit.
HRH Quality Control app
This project is a graphical calculator for solving equations using the Newton Method and finding function minima using the Gradient Descent algorithm, utilizing PySide6, SymPy, and Matplotlib.
Application of four different numerical methods to compute the square root of 2
Numeric methods laboratory works
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