Tech Xplore

New graph attention network models higher-order relationships in complex graph data

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

Interpretability in deep learning for finance: A case study for the Heston model

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known Heston option pricing model as a benchmark, researchers show that global ...

WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
EurekAlert!

Making light “think” in negatives: A fully real-valued optical chip for generative model

Researchers have developed a fully real-valued, end-to-end optical neural network chip that overcomes the physical limitation ...
Semiconductor Engineering

Hypergraph-based Techniques To Map Spiking Neural Networks on Neuromorphic HW (Politecnico di Milano)

A new technical paper titled “A Case for Hypergraphs to Model and Map SNNs on Neuromorphic Hardware” was published by ...