AI techniques excel at solving complex equations in physics, especially inverse problems

Differential equations are fundamental tools in physics: they are used to describe phenomena ranging from fluid dynamics to general relativity. But when these equations become stiff (i.e. they involve ...
InfoWorld

A brief history of AI

Artificial intelligence has taken many forms over the years and is still evolving. Will machines soon surpass human knowledge ...
GitHub

generative-neural-network

A simulation model for the digital reconstruction of 3D root system architectures. Integrated with a simulation-based inference generative deep learning model.
powerelectronicsnews

Modeling SiC MOSFETs with Neural Networks

A recent Nature study shows that separated artificial neural networks can accurately model SiC MOSFETs using minimal training data. Silicon carbide MOSFETs are increasingly replacing traditional ...
IEEE

Efficient and Privacy-Preserving Artificial Neural Network Model Training With Separated Data in IoT

Abstract: Machine learning models based on artificial neural networks (ANNs) have been widely adopted to support diverse complex applications. However, the training of such models heavily relies on ...
C&EN

GSH and Halides Directed Controllable Synthesis of Chiral Gold Nanostars for Sensitive Diagnosis of Nephritis Types Using SERS and Transformer Neural Network

Institute of Digitized Medicine and Intelligent Technology, Wenzhou Medical University, Wenzhou 325000, P. R. China ...
IEEE

Artificial Neural Network Classifier for Dynamic Load Alteration Analysis in Active Distribution Network

Abstract: The presented research paper proposes Dynamic Load Alteration (DLA) analysis in Active Distribution Network (ADN) using Artificial Neural Network (ANN) classifier. The proposed problem as ...