While artificial intelligence (AI) has made remarkable achievements in domains like image recognition and natural language processing, it encounters fundamental challenges when trying to deal with ...

AI-driven operator learning models like Fourier Neural Operator and DeepONet are redefining simulation speed, producing results in seconds instead of hours. Coupled with automation tools such as ...

(a). Given the PDE initial fields, PIANO first infers the physical invariant (PI) embedding via the PI encoder, then integrates it into the neural operator to obtain a personalized operator. After ...

Engineers have uncovered an unexpected pattern in how neural networks -- the systems leading today's AI revolution -- learn, suggesting an answer to one of the most important unanswered questions in ...

A new technical paper titled “DeepOHeat: Operator Learning-based Ultra-fast Thermal Simulation in 3D-IC Design” was published (preprint) by researchers at UCSB and Cadence. “Thermal issue is a major ...

AI models trained on physics are slashing the time needed for complex engineering simulations, enabling faster design iterations across industries like automotive, aerospace, and materials science. By ...

Researchers used the world's fastest supercomputer for open science to train an artificial intelligence model that captures ...