A $1 million prize awaits anyone who can show where the math of fluid flow breaks down. With specially trained AI systems, ...

Abstract: Nonlinear equation systems are ubiquitous in a variety of fields, and how to tackle them has drawn much attention, especially dynamic ones. As a particular class of recurrent neural network, ...

This repository provides a solution to the standard Capacitated Vehicle Routing Problem with Time Windows (CVRPTW). In a CVRPTW, we aim to optimize the routes of a fleet of vehicles serving customers ...

For more than a century, scientists have wondered why physical structures like blood vessels, neurons, tree branches, and ...

Abstract: In this study, physics-informed graph residual learning (PhiGRL) is proposed as an effective and robust deep learning (DL)-based approach for 3-D electromagnetic (EM) modeling. Extended from ...

Objective metrics, intelligent test generation, and data-driven insights for LLM apps Ragas is your ultimate toolkit for evaluating and optimizing Large Language Model (LLM) applications. Say goodbye ...

Numerov’s numerical method is developed in a didactic way by using Python in its Jupyter Notebook version 6.0.3 for three different quantum physical systems: the hydrogen atom, a molecule governed by ...

When you purchase through links on our site, we may earn an affiliate commission. Here’s how it works. In October 2024, news broke that Facebook parent company Meta had cracked an "impossible" problem ...

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 ...