Knowledge distillation is an increasingly influential technique in deep learning that involves transferring the knowledge embedded in a large, complex “teacher” network to a smaller, more efficient ...

In an increasingly interconnected world, understanding the behavior and structure of complex networks has become essential across disciplines. These ...

The field of systems neuroscience increasingly seeks to understand how distributed neural populations interact to support complex cognitive functions such ...

The results include a comparison between two different basis functions for temporal selectivity and how these generate different predictions for the dynamics of neural populations. The conclusions are ...

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

Scientists propose a new way of implementing a neural network with an optical system which could make machine learning more sustainable in the future. In a new paper, the researchers have demonstrated ...

Cheng Lyu is the winner of the 2025 Eppendorf & Science Prize for Neurobiology for her work in understanding how neural circuits assemble with such remarkable precision during development. Neural ...

Scientists propose a new way of implementing a neural network with an optical system which could make machine learning more sustainable in the future. The researchers at the Max Planck Institute for ...

Researchers have unveiled a new generation of photonic computing chips capable of performing real‑time learning and decision‑making using only light-based processes. Photonic chips deliver real‑time ...

MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, released a core quantum machine learning technology oriented toward sequential learning tasks—the ...

Research Compounds Scientists Study for Brain Function and Cognitive Performance Modern neuroscience research continues ...