Nature

A scalable framework for learning the geometry-dependent solution operators of partial differential equations

Solving partial differential equations (PDEs) with numerical methods has a pivotal role in a wide variety of disciplines in science and engineering, with applications such as topology and design ...
EurekAlert!

PIANO: a new operator learning framework that deciphers and incorporates invariants from the PDE series via self-supervised learning and attention technique, achieving superior ...

(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 ...
Nature

U-DeepONet: U-Net enhanced deep operator network for geologic carbon sequestration

Learning operators with deep neural networks is an emerging paradigm for scientific computing. Deep Operator Network (DeepONet) is a modular operator learning framework that allows for flexibility in ...
Medical Xpress

AI framework speeds up brain neuron modeling

Cedars-Sinai investigators worked with a multi-institutional team to develop a new artificial intelligence framework that can accurately, quickly and efficiently create virtual models of brain neurons ...
EurekAlert!

Learning neural operators on Riemannian manifolds

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 ...
Semiconductor Engineering

3D-IC: Operator Learning Framework For Ultra-Fast 3D Chip Thermal Prediction Under Multiple Chip Design Configurations

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 ...