Microsoft's 2029 quantum supercomputer ambitions may have hit a roadblock, as critics claim the company's 2025 quantum ...

Purdue University’s Artificial Intelligence Microcredentials offer quick and convenient online courses that cover the fundamentals of artificial intelligence and its applications. Every course ...

Python provides an integrated analytical ecosystem for solving core supply chain problems such as demand forecasting, inventory planning, transportation routing, and operational simulation.

"It's like Gmail for your coding agents!" A mail-like coordination layer for AI coding agents, exposed as an MCP server with 37 tools and 25 resources, Git-backed archive, SQLite indexing, an ...

Asphalt is a complex multi-component material widely used in road engineering, waterproofing and other applications 1,2. Based on its compositional characteristics, asphalt is typically divided into ...

Influence Maximization (IM) is a fundamental problem in network science with applications in viral marketing, information dissemination, cybersecurity, and epidemiology. Classical IM solvers often ...

Understanding the mechanism of how neural networks learn features from data is a fundamental problem in machine learning. Our work explicitly connects the mechanism of neural feature learning to a ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Two of the most widely used electronic-structure theory methods, namely, Hartree–Fock ...

You are free to share (copy and redistribute) this article in any medium or format and to adapt (remix, transform, and build upon) the material for any purpose, even commercially within the parameters ...

Physics-Informed Neural Networks (PINN) are neural networks encoding the problem governing equations, such as Partial Differential Equations (PDE), as a part of the neural network. PINNs have emerged ...