QNNs achieved 95 percent accuracy, while QSVMs reached 94 percent, both surpassing classical machine learning methods, which ...

Imagine tracking your heartbeat without strapping on a smartwatch or touching any gadget, just by sitting within range of ...

The integration of deep learning in biodiesel research accelerates feedstock evaluation and optimizes production, making it ...

How rapidly gene expression in a single cell changes over time can provide insight into how cells might become more specialized. A new method to calculate RNA velocity, developed by researchers at ...

AI transforms RF engineering through neural networks that predict signal behavior and interference patterns, enabling ...

The Pulse-Fi system is highly accurate, achieving clinical-level heart rate monitoring with ultra low-cost WiFi devices, making it useful for low resource settings. The system works with the person in ...

This study presents valuable computational findings on the neural basis of learning new motor memories without interfering with previously learned behaviours using recurrent neural networks. The ...

What if AI could keep learning like a human brain, in new conditions even after it was used, deployed & put to use in real life? A Liquid Neural Network (LNN) is a new type of artificial intelligence ...

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 ...

Abstract: It is known that the learning rate is the most important hyper-parameter to tune for training deep neural networks. This paper describes a new method for setting the learning rate, named ...

Critical network states and neural plasticity enable adaptive behavior in dynamic environments, supporting efficient information processing and experience-dependent learning. Synaptic-weight-based ...