Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, R

Numerical methods implementation in MATLAB.

Classic problems in chemical engineering solved with matlab

Obtaining the best coefficients of Inverse Dynamics Controller, for a dynamical system, with Optimization Algorithms.

暑期研究：神经网络解偏微分方程（Neural networks for solving differential equations）

Optimization Problems Toolbox

MFM community development code

Differential Equations Guide

The optimization field suffers from the metaphor-based “pseudo-novel” or “fancy” optimizers. Most of these cliché methods mimic animals' searching trends and possess a small contribution to the optimization process itself. Most of these cliché methods suffer from the locally efficient performance, biased verification methods on easy problems, an…

A MATLAB suite of initial value problems

Interactive courseware module that addresses the qualitative analysis of ordinary differential equations taught in mathematics courses.

A collection of numerical methods in MATLAB.

MATLAB implementation of the Perona-Malik Diffusion (anisotropic diffusion). The algorithm is designed to denoise images while keeping edges intact. Both explicit and semi-implicit implementations can be found in the repository

n dimensional Brownian motion with an arbitrary mean and Variance Covariance matrix.

[Computer Modeling] SIR/SIRS/SIRQ/ISIR/SEIR compartmental models for numerical epidemic modelling in MATLAB.

a gradient-based optimisation routine for highly parameterised non-linear dynamical models

Object-oriented constructor of finite difference schemes

Implementations of various Algorithms used in Numerical Analysis, from root-finding up to gradient descent and numerically solving PDEs.

A collection of classical algorithms to solve ODEs and boundary value problems

Mathematical model based on the numerical analysis of ordinary differential equations for the capture of satellite positions and velocities