Transformers are a neural network (NN) architecture, or model, that excels at processing sequential data by weighing the ...
Deep Learning with Yacine on MSN
Network in Network (NiN) Explained – Deep Neural Network Tutorial with PyTorch
Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...
Welcome to the Zero to Mastery Learn PyTorch for Deep Learning course, the second best place to learn PyTorch on the internet (the first being the PyTorch documentation). 00 - PyTorch Fundamentals ...
Abstract: Equivariant quantum graph neural networks (EQGNNs) offer a potentially powerful method to process graph data. However, existing EQGNN models only consider the permutation symmetry of graphs, ...
Abstract: The pinching-antenna system is a novel flexible-antenna technology, capable of both mitigating large-scale path loss and reconfiguring antenna arrays adaptively. Its core principle relies on ...
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