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

This Research Topic is the second volume in the series: Information Theory Meets Deep Neural Networks: Theory and Applications. The previous volume can be viewed here: Volume I Deep Neural Networks ...

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 ...

In 1930, a young physicist named Carl D. Anderson was tasked by his mentor with measuring the energies of cosmic ...

AI-native air interfaces represent a shift from mathematical models to learned representations at the PHY layer.

Abstract: We introduce a novel deep graphical representation that integrates game theory (GT) principles with the laws of statistical physics (SP), enabling feature extraction and pattern ...

ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...

Bodies keep surfacing — and so do questions. There's a dark current in Houston's bayous this year, with 16 bodies recovered, five of them in the same week last month. City leaders are downplaying ...

Department of Brain and Cognitive Sciences & McGovern Institute, MIT, Cambridge, United States Integrative Computational Neuroscience Center and Yang-Tan Collective, MIT, Cambridge, United States ...

Not revised: This Reviewed Preprint includes the authors’ original preprint (without revision), an eLife assessment, and public reviews. This is a theoretical study addressing the problem of ...