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

A research team at Duke University has developed a new AI framework that can uncover simple, understandable rules that govern some of the most complex dynamics found in nature and technology. The AI ...

It remains an open question when a commercial quantum computer will emerge that can outperform classical (non-quantum) machines in speed and energy efficiency while solving real-world combinatorial ...

Abstract: In this article, we study system of Riccati equations using the operational matrix method. This system is important since it has several applications in different areas such as random ...

CEETA PG 2026 Syllabus: The Anna University, Chennai, conducts the Common Engineering Entrance Test and Admissions (CEETA PG) for admission to M.E./ M.Tech./ M.Arch./ M.Plan offered at University ...

Abstract: Recently, analog matrix inversion circuits (INV) have demonstrated significant advantages in solving matrix equations. However, solving large-scale sparse tridiagonal linear systems (TLS) ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of computing a matrix inverse using the Newton iteration algorithm. Compared to other algorithms, Newton ...

This repository allows you to solve forward and inverse problems related to partial differential equations (PDEs) using finite basis physics-informed neural networks (FBPINNs). To improve the ...

To learn math, students must build a mental toolbox of facts and procedures needed for different problems. But students who can recall these foundational facts in isolation often struggle to use them ...

Presenting an algorithm that solves linear systems with sparse coefficient matrices asymptotically faster than matrix multiplication for any ω > 2. Our algorithm can be viewed as an efficient, ...