Supports safe lifecycle sequencing, synchronous command API, and a background reader thread that demultiplexes asynchronous measurement lines from command responses.

Abstract: This study introduces a digital twin model approach with Graph Neural Networks (GNNs) to forecast white blood cell (WBC) and absolute neutrophil count (ANC) levels during 6-mercaptopurine (6 ...

Department of Biomedical Engineering and Health, KTH Royal Institute of Technology, Stockholm, Sweden Introduction: The classification of lesion types in Digital Breast Tomosynthesis (DBT) images is ...

Abstract: Investigating the temporal behavior of digital circuits is a crucial step in system design, usually done via analog or digital simulation. Analog simulators like SPICE iteratively solve the ...

Neural networks aren’t the only game in artificial intelligence, but you’d be forgiven for thinking otherwise after the hot streak sparked by ChatGPT’s arrival in 2022. That model’s abilities, ...

This project is a companion to the article “Wrestling with the Python: Why AI Needs Digital Humanities to Make Sense of the World” It gathers practical tools, methods, and references from Digital ...

A new international study has introduced Curved Neural Networks—a new type of AI memory architecture inspired by ideas from geometry. The study shows that bending the "space" in which AI "thinks" can ...

Spiking neural networks (SNNs) have recently demonstrated significant progress across various computational tasks, due to their potential for energy efficiency. Neural radiance fields (NeRFs) excel at ...

Innatera’s Pulsar blends analog and digital SNN accelerators to deliver always-on neural-network operation for low-power applications. 1. Innatera’s Pulsar system-on-chip incorporates analog and ...