Something extraordinary has happened, even if we haven’t fully realized it yet: algorithms are now capable of solving ...

Please be aware that this is a beta release. Beta means that the product may not be functionally or feature complete. At this early phase the product is not yet expected to fully meet the quality, ...

Service provider networks have grown well beyond the traditional offerings of video and residential broadband, and meeting the needs of today’s subscriber will depend on how these networks integrate ...

Abstract: Spiking Neural Networks (SNNs) have emerged as a promising alternative to traditional Artificial Neural Networks (ANNs) due to their biological interpretability. SNNs process input ...

Massive computing systems are required to train neural networks. The prodigious amount of consumed energy makes the creation of AI applications significant polluters ...

Learn how forward propagation works in neural networks using Python! This tutorial explains the process of passing inputs through layers, calculating activations, and preparing data for ...

STM-Graph is a Python framework for analyzing spatial-temporal urban data and doing predictions using Graph Neural Networks. It provides a complete end-to-end pipeline from raw event data to trained ...

Understand the Maths behind Backpropagation in Neural Networks. In this video, we will derive the equations for the Back Propagation in Neural Networks. In this video, we are using using binary ...

Background In an ophthalmology emergency department, determining treatment urgency is crucial for patient safety and the efficient use of resources. The aim of this study was to use artificial ...