Neural architecture search promises to speed up the process of finding neural network architectures that will yield good models for a given dataset. Neural architecture search is the task of ...

Deep neural networks have a huge advantage: They replace “feature engineering”—a difficult and arduous part of the classic machine learning cycle—with an end-to-end process that automatically learns ...

Neural Architecture Search (NAS) is an emerging area focused on automating the design of neural network architectures. The overarching goal of NAS research is to discover optimal network architectures ...

Image courtesy by QUE.com In the ever-evolving world of artificial intelligence, deep neural networks (DNNs) have ...

This book explores the interdisciplinary project that brings the long tradition of humanistic inquiry in architecture together with cutting-edge research in artificial intelligence. The main goal of ...

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This blog post is the second in our Neural Super Sampling (NSS) series. The post explores why we introduced NSS and explains its architecture, training, and inference components. In August 2025, we ...

SHENZHEN, China, March 17, 2025 /PRNewswire/ -- MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, they are researching CV-QNN (Continuous Variable ...

Eight names are listed as authors on “Attention Is All You Need,” a scientific paper written in the spring of 2017. They were all Google researchers, though by then one had left the company. When the ...