A Python desktop application for solving mathematical equations using various numerical methods. This interactive tool provides a modern GUI for inputting equations and visualizing results through interactive plots. Features include solution history tracking, customizable settings, and PDF export capabilities.

🔍 Implement flow matching for efficient few-step generation with this minimal Pi-Flow solution, enabling easy reproduction of distillation results.

A library bridges port-based thinking to numerics.

A small python library that supports differentiation and solving (simple) equations

Comparison of Steepest Descent and Conjugate Gradient iterative solvers for SPD linear systems with experimental analysis and LaTeX paper

Applied Numerical Linear Algebra techniques to Voting Theory.

Datrix es una app web desarrollada con Python y Streamlit, orientada estudiantes de Ingeniería, Física Médica, Diagnóstico por Imágenes.

Sequential and parallel implementation for the Block Coordinate Descent (BCD) method

Python-based Derivative-Free Optimization with Bound Constraints

Python-based Derivative-Free Optimizer for Least-Squares

Python trust-region subproblem solvers for nonlinear optimization

Like `requests` for mathematical computing, making complex math feel simple.

First explicit curvature correction formula for fractional Laplacians on curved manifolds. Complete proof via heat kernel expansion, validated computationally on S². Applications in anomalous diffusion, thermal field theory, and curved spacetime physics.

Collection of third and fourth order extended stability runge kutta schemes

Proyecto de curso de la asignatura Álgebra Lineal.

Data Preprocessing & Feature Engineering Pipeline

This project aims to solve the differential equation for an RLC circuit numerically using Euler's Method.

Evaluating several new approaches to improve convergence of Randomized Kaczmarz (RK) for consistent ill-conditioned systems. This project explores the availability of convergence information among pairwise row differences and analyzes sampling techniques that involve clustering and spectral analysis.

This repository contains a robust and flexible Python package for solving ordinary differential equations (ODEs). It supports both Runge–Kutta schemes (explicit, DIRK) and BDF multistep methods, with adaptive time-stepping and strong support for sparse Jacobians--making it well-suited for large-scale and stiff problems.