This repository contains the code and models for our paper "Investigating and Mitigating Failure Modes in Physics-informed Neural Networks(PINNs)"

Derivation and construction of a thermodynamic phase diagram for ternary alloy systems with 2 or 3 phases

Gitcoin Bounty - Open Defi Hackathon Submission for Parallel Swap in Ref Finance on Near.

EPITA Course Materials

Notes from Mathematics for Machine Learning and Data Science Specialization

Implementation of Support Vector Machine algorithm using Lagrange Multipliers method for solving non-linear constrained optimization problems.

DRIP Numerical Optimizer is a collection of Java libraries for Numerical Optimization and Spline Functionality.

Machine Learning for Data 3141 Reichman University Spring 2022 - 6 Homework Projects

A Lagrange Dual Learning Framework for Solving Constrained Inverse Kinematics Tasks (Project for 6.881 Spring 2020, Optimization for Machine Learning)

In this project, we modeled the motion of a ball on a rotating parabolic wire using the Lagrange multiplier method. We derived and solved the system of differential equations via the Constraint Stabilization method, analyzing the results using Python with NumPy, SciPy, and Matplotlib for computation and visualization.

Ce Travail vise à reproduire les méthodes statistiques utilisées dans un article de recherche qui a exploré l’impact de COVID-19 sur la volatilité de l’indice boursier marocain (MASI).

SM Model Optimization: Lagrange and MIP

A collection of tools to used to evaluate dynamical systems with nonholonomic constraints.

A codebase for a traffic optimization research project.

Graph-Lagrange is an interactive Python tool for analyzing and visualizing mathematical functions in 1D and 2D. It allows users to compute critical points, local maxima, minima, saddle points, inflection points, and limits for single-variable and multivariable functions. The project also supports constrained optimization using Lagrange multipliers.

Material from the course of Static and Dynamic Optimization at ENSEM - Université de Lorraine.

Lagrange Multipliers in Portfolio Optimization with Mixed Constraints

GUI Visualizations of Singular Value Decomposition, Gradient Descent, Lagrange Multipliers using JS Libraries