minimization-algorithm

The fastest open-source C++17 optimization library for unconstrained nonlinear problems. Header-only, single dependency. Highest reliability, composable function expressions, unconstrained and constrained solvers.

Repository for the Theriak-Domino suite of programs.

collection of numerical optimization methods

A library for fitting a sequence of electrochemical impedance spectra (JAX version).

Designing recurrent neural networks by unfolding an l1-l1 minimization algorithm

➗ This work presents a thorough analysis of a quadratic optimization model, confirming convexity, coercivity, and the exact global minimum. It compares gradient descent and Newton’s method, highlighting Newton’s superior efficiency when the Hessian is invertible.

a python code that uses the randomness of neural network training to find the ground state of a harmonic oscillator and its energy

Optimization Methods in Management Science assignment: Solving a vehicle routing problem

Light-weight Levenberg Marquardt fitting routing on GPUs with CUDA

A tic tac toe game with an AI opponent using minimax algorithm and alpha-beta pruning. Reference link : https://en.wikipedia.org/wiki/Minimax#Minimax_algorithm_with_alternate_moves

example code for how to run a best-of-random differential evolution optimization method in Fortran

Una implementación inicial del algoritmo de Quine McCLuskey para reducir expresiones logicas.

Automate Quantum Espresso routines

Frontend de la aplicacion de minimizacion de AFD

Project to assist students in writing their lab work for the 1st year, 2nd semester (discrete mathematics).

These are my university projects on the discipline "Numerical methods". I implemented various algorithms of numeric calculations such as: interpolation, approximation, integral calculation, solving equations, solving systems of linear algebraic equations (SLAE), minimization of quadratic function

This is a repository associated with the chapter book "Towards optimal sampling for learning sparse approximations in high dimensions" by Ben Adcock, Juan M. Cardenas, Nick Dexter and Sebastian Moraga to be published by Springer in late 2021, available at https://arxiv.org/abs/2202.02360

Given a network, equipped with a specific total and strict order, we get the minimal "round trip" traversal length. It always converges, at quadratic cost.

🧮 Also known as the Quine-McCluskey method