Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
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 ...
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 ...
Researchers from the University of Tokyo in collaboration with Aisin Corporation have demonstrated that universal scaling laws, which describe how the properties of a system change with size and scale ...
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Unhackable metasurface holograms: Security technology can lock information with light color and distance
A research team led by Professor Junsuk Rho at POSTECH (Pohang University of Science and Technology) has developed a secure ...
Learn how to build a fully connected, feedforward deep neural network from scratch in Python! This tutorial covers the theory, forward propagation, backpropagation, and coding step by step for a hands ...
Lightweight convolutional neural networks improved lung cancer classification accuracy in histopathological images while ...
Joint calibration to the Standard & Poor’s 500 (SPX) and Chicago Board Options Exchange (CBOE) Volatility Index (VIX) market data can be computationally burdensome, especially when the standard course ...
Both a wildfire and activity of digital “neurons” exhibit a phase transition from an active to an absorbing phase. Once a system reaches an absorbing phase, it cannot escape from it without outside ...
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