Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is the ...
The world of artificial intelligence is moving beyond the cloud and into our everyday devices from smart sensors to robotics and AR/VR headsets. One of the key components that enables this shift is a ...
Baptist Medical Center, Department of Behavioral Health, Jacksonville, FL, United States Introduction: This study investigates four subdomains of executive functioning—initiation, cognitive inhibition ...
Abstract: The efficient training of Transformer-based neural networks on resource-constrained personal devices is attracting continuous attention due to domain adaptions and privacy concerns. However, ...
Softmax ensures the sum of all output probabilities is 1, making it ideal for multi-class classification, whereas Sigmoid treats each class independently, leading to probabilities that don’t sum to 1.
Recent work has established an alternative to traditional multi-layer perceptron neural networks in the form of Kolmogorov-Arnold Networks (KAN). The general KAN framework uses learnable activation ...
Background—Because renal function is affected by chronic heart failure (CHF) and it relates to both cardiovascular and hemodynamic properties, it should have additional prognostic value. We studied ...
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