There are 1 repository under newton-method topic.
Newton and Quasi-Newton optimization with PyTorch
High-performance and differentiation-enabled nonlinear solvers (Newton methods), bracketed rootfinding (bisection, Falsi), with sparsity and Newton-Krylov support.
Python machine learning applications in image processing, recommender system, matrix completion, netflix problem and algorithm implementations including Co-clustering, Funk SVD, SVD++, Non-negative Matrix Factorization, Koren Neighborhood Model, Koren Integrated Model, Dawid-Skene, Platt-Burges, Expectation Maximization, Factor Analysis, ISTA, FISTA, ADMM, Gaussian Mixture Model, OPTICS, DBSCAN, Random Forest, Decision Tree, Support Vector Machine, Independent Component Analysis, Latent Semantic Indexing, Principal Component Analysis, Singular Value Decomposition, K Nearest Neighbors, K Means, Naïve Bayes Mixture Model, Gaussian Discriminant Analysis, Newton Method, Coordinate Descent, Gradient Descent, Elastic Net Regression, Ridge Regression, Lasso Regression, Least Squares, Logistic Regression, Linear Regression
A next-gen solver for nonlinearly constrained nonconvex optimization. Modular and lightweight, it unifies iterative methods (SQP vs interior points) and globalization techniques (filter method vs merit function, line search vs trust region method) in a single framework. Competitive against IPOPT, filterSQP, SNOPT, MINOS and CONOPT
Drawing Newton's fractal using pure js, rust-wasm, SIMDs, threads and GPU
Basic Machine Learning implementation with python
Hessian-based stochastic optimization in TensorFlow and keras
Python and MATLAB code for Stein Variational sampling methods
Implementation and visualization (some demos) of search and optimization algorithms.
If you find any errors in the work of algorithms, you can fix them by creating a pull request
Optimization course for MSAI at MIPT
Prototyping of matrix free Newton methods in Julia
This is a Numerical Analysis course project, implementing numerical analysis methods.
Implementation and analysis of convex optimization algorithms
Optimization course assignments under the supervision of Dr. Maryam Amirmazlaghani
Newton’s second-order optimization methods in python
A Unified Pytorch Optimizer for Numerical Optimization
Collection of methods for numerical analysis and scientific computing, including numerical root-finders, numerical integration, linear algebra, and data visualization. Created for APPM4600 at CU Boulder.
Polynomial essentials for Golang including real root isolation, complex root solving methods, root bounds, and derivatives.
C++11 implementation of numerical algorithms described in Numerical Analysis by Richard L. Burden and J. Douglas Faires
Numerical methods algorithms implementation
Computation of periodic orbits of non-autonomous systems and fixed points of maps using Newton method
Its Newton Vs the Machines!
Newton fractal in openframeworks, with shaders. (inspired by: 3b1b)
Optimization Techniques Lab Dump
Projects from MATH 555, Computational Algebraic Geometry taken Fall of 2021
A Python Implementation of Polynomials and algorithms associated with it
Моделирование различных динамических процессов с использованием методов вычислительной математики
Implementation of Unconstrained minimization algorithms. These are listed below:
a Python implementation of various optimization methods for functions using Streamlit.
A Swift Library for Newton Raphson Method
Project II from CISC.820.01 - Quantitative Foundations