WiMi Releases Next-Generation Quantum Convolutional Neural Network Technology for Multi-Channel Supervised Learning

WiMi Releases Next-Generation Quantum Convolutional Neural Network Technology for Multi-Channel Supervised Learning BEIJING, Jan. 05, 2026––WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the ...
Devdiscourse

AI takes the helm in power systems facing renewable and carbon pressures

AI methods are increasingly being used to improve grid reliability. Physics-informed neural networks are highlighted as a ...
IEEE

Multigranularity Deep Graph Convolutional Neural Network Node Clustering Leveraging Spatial Information

Abstract: In the era of information explosion, clustering analysis of graph-structured data and empty graph-structured data is of great significance for extracting the intrinsic value of data. From ...
IEEE

A Novel Low-resource Graph Convolutional Neural Network Approach for Entity Recognition

Abstract: With the rise of large language models in natural language processing, the use of various generative large language models for entity recognition has become a cutting-edge research approach.
Live Science

What are neural processing units (NPUs) and why are they so important to modern computing?

Neural processing unts (NPUs) are the latest chips you might find in smartphones and laptops — but what are they ard why are they so important? When you purchase through links on our site, we may earn ...
Frontiers

Association prediction of lncRNAs and diseases using multiview graph convolution neural network

1 College of Computer Science and Engineering, Changsha University, Changsha, Hunan, China 2 Department of Information and Computing Science, College of Mathematics, Changsha University, Changsha, ...
Scientific Research Publishing

Phan, A.V., Nguyen, M.L., Nguyen, Y.L.H. and Bui, L.T. (2018) DGCNN: A Convolutional Neural Network over Large-Scale Labeled Graphs. Neural Networks, 108, 533-543.

ABSTRACT: Point cloud-based 3D object detection is a key technology in autonomous driving and mobile robot perception systems. However, the sparsity and irregularity of point cloud data result in poor ...
Microsoft

Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties.

The use of machine learning methods for accelerating the design of crystalline materials usually requires manually constructed feature vectors or complex transformation of atom coordinates to input ...