a lightweight header-only C++17 library of numerical optimization methods for nonlinear functions based on Eigen

Repository for the Theriak-Domino suite of programs.

collection of numerical optimization methods

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

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

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

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

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

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).

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

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

Automate Quantum Espresso routines

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

Various algorithms, without explanation of their work

This project aims at providing the optimal solution for minimum transportation costing based on two decision variables along with a pictorial overview of the problem. The project uses Excel for dataset cleaning and manipulation as well as python programming for simplex solution and finally, SAS Visual Analytics for visualization.

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.