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 ...

It seems as if not a week goes by in which the artificial intelligence concepts of deep learning and neural networks make it into media headlines, either due to an exciting new use case or in an ...

Parth is a technology analyst and writer specializing in the comprehensive review and feature exploration of the Android ecosystem. His work is distinguished by its meticulous focus on flagship ...

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

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 ...

During my first semester as a computer science graduate student at Princeton, I took COS 402: Artificial Intelligence. Toward the end of the semester, there was a lecture about neural networks. This ...

Lightweight convolutional neural networks improved lung cancer classification accuracy in histopathological images while ...

The TLE-PINN method integrates EPINN and deep learning models through a transfer learning framework, combining strong physical constraints and efficient computational capabilities to accurately ...

Neuroscience, behavioral science, and medical research are accelerating with the help of the predictive power of artificial intelligence (AI) machine learning. A new peer-reviewed study published in ...

Bridging speed and accuracy in radiation therapy QA Led by Professor Fu Jin, the study addresses a critical challenge in ...