From ‘Optical Synapses’ to a ‘Photonic Brain’ — Integrated Photonic Neural Networks Toward Low-Power General-Purpose

SHANNON, CLARE, IRELAND, February 5, 2026 /EINPresswire.com/ -- A new publication from Opto-Electronic Technology; DOI ...

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 ...

Glass Imaging Announces Availability of GlassAI™ RAW Video Neural ISP Pipeline on Qualcomm Chipsets

GlassAI Enables Real-Time RAW Video Processing on Snapdragon® 8 Elite (Gen 5) Platforms The Snapdragon 8 Elite (Gen 5) ...

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 ...
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PolyU develops novel AI graph neural network models to unravel interdisciplinary complexities in image recognition and neuroscience

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...
Duke Pratt School of Engineering

Mapping Behavior with Machine Learning

By transforming movement into data, Timothy Dunn is reshaping how scientists can study behavior and the brain.

RRAM hasn't delivered yet, but stacked memory is being pitched to run neural networks in place

A team at the University of California, San Diego has redesigned how RRAM operates in an effort to accelerate the execution ...

Openmind Networks Advances Global Messaging Security as OpenProtectAI Wins Top Honors for AI-Powered Fraud Detection

OpenProtectAI recognized as Platinum Winner for Best Messaging Fraud Mitigation and Gold Winner for Best AI-Powered ...
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 ...

AI method accelerates liquid simulations by learning fundamental physical relationships

Researchers at the University of Bayreuth have developed a method using artificial intelligence that can significantly speed up the calculation of liquid properties. The AI approach predicts the ...
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Transfer learning empowers material Z classification with muon tomography

Researchers have demonstrated, for the first time, that transfer learning can significantly enhance material Z-class identification in muon tomography, even in scenarios with limited or completely ...