Deep learning models, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs) are designed to partly emulate the functioning and structure of biological neural networks. As a ...

To this end, we introduce a novel attractor-based neural network to realize on-chip movement decoding for next-generation portable RPHs. The proposed architecture comprises an encoder, an attention ...

In the world of particle physics, where scientists unravel the mysteries of the universe, artificial intelligence (AI) and ...

A complete, professional neural network implementation built entirely from scratch using only NumPy for MNIST digit classification. This project achieves 98.06% test accuracy with a clean, ...

More specifically, our approach forms vectors which represent the input words as well as the neural network's states at different time steps into matrices when it processes one sentence, and as a ...