Neural architecture search (NAS) and machine learning optimisation represent rapidly advancing fields that are reshaping the way modern systems are designed and deployed. By automating the process of ...

Over the past decades, computer scientists have developed increasingly advanced artificial intelligence (AI) systems that ...

Recent advances in neural network design have spurred the development of energy-efficient architectures for speech recognition, a field that underpins a range of modern applications from smart ...

NAS methods can generally be classified based on tailored designs from the following aspects: search space, search strategy, and evaluation strategy. In particular, search space can be further ...

MicroCloud Hologram Inc. has announced the creation of a noise-resistant Deep Quantum Neural Network (DQNN) architecture, which aims to advance quantum computing and enhance the efficiency of quantum ...

How do electrical signals become "about" something? Through purely physical processes, neural networks transform activity ...

A new technical paper titled “Optimizing event-based neural networks on digital neuromorphic architecture: a comprehensive design space exploration” was published by imec, TU Delft and University of ...

Avian species have become important model organisms in behavioral neuroscience due to their capacity for complex cognitive functions supported by ...

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known ...

In their classic 1998 textbook on cognitive neuroscience, Michael Gazzaniga, Richard Ivry, and George Mangun made a sobering observation: there was no clear mapping between how we process language and ...