Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...
As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...
Deep brain stimulation (DBS) improves motor symptoms of Parkinson's disease by modulating a specific brain network that is mainly active in the fast beta frequency range (20 to 35 Hz). This conclusion ...
The signals that drive many of the brain and body's most essential functions—consciousness, sleep, breathing, heart rate and motion—course through bundles of "white matter" fibers in the brainstem, ...
A new international study points to a specific brain network as the core driver of Parkinson’s disease. Scientists found that ...
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Dijkstra’s algorithm won’t be replaced in production routers any time soon
Researchers have found a new approach to finding shortest paths, but it's complex Systems Approach Last year a couple of people forwarded to me the same article on a new method of finding shortest ...
Abstract: Despite the wide variety of applications and use cases that can be solved with the help of machine learning algorithms, researchers have yet to develop a general artificial intelligence ...
Abstract: Accurate imputation of missing data is crucial in the Industrial Internet-of-Things (IIoT), where operations are often compromised by noisy samples from harsh environments. Traditional ...
State-of-the-art techniques for pavement performance evaluation have attracted considerable attention in recent years. Artificial Neural Networks (ANNs) can simulate the human brain to discover hidden ...
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