“I was curious to establish a baseline for when LLMs are effectively able to solve open math problems compared to where they ...

This repository contains a complete collection of implementations for various Numerical Methods used in computational mathematics. The project covers a wide range of topics including linear and ...

Where Winds Meet players are taking a novel approach to solving riddles by… simply telling the game's AI-powered chatbot NPCs that they have solved the game's riddles. The Wuxia open-world ...

This paper introduces the Julia programming language as a dynamic, cost-effective, and efficient framework for implementing structural analysis packages. To achieve this, the finite element method was ...

The program runs each method 100 times to measure average execution time and compares the performance against expected computational complexity. Cramer's Rule computes each variable xᵢ as the ratio ...

Analog computers are systems that perform computations by manipulating physical quantities such as electrical current, that map math variables, instead of representing information using abstraction ...

A UNSW Sydney mathematician has discovered a new method to tackle algebra's oldest challenge—solving higher polynomial equations. Polynomials are equations involving a variable raised to powers, such ...

Abstract: A new analytical method for finding the general solution of the nth-order linear differential equation with variable coefficients is given based on generalizing the idea of differential ...

Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on an implementation of the technique that emphasizes simplicity and ease-of-modification over robustness and ...

Computing the inverse of a matrix is one of the most important operations in machine learning. If some matrix A has shape n-by-n, then its inverse matrix Ai is n-by-n and the matrix product of Ai * A ...