The rapid development of artificial intelligence (AI), big data analytics ... Inspired by cognitive and computational methods of animal brains, the third-generation neural network, SNN, makes ...

Network architectures and learning principles have been critical in developing complex cognitive capabilities in artificial neural ... the network motifs in SNN, the Motif mask is used to mask the ...

Abstract: In Collaborative Intelligence (CI), the Artificial Intelligence (AI ... Previous research has demonstrated that Spiking Neural Network (SNN)-based SC models exhibit greater robustness on ...

are emerging as a promising energy-efficient alternative to traditional artificial neural networks (ANNs) due to their spike-driven paradigm. However, recent research in the SNN domain has mainly ...

are emerging as a promising energy-efficient alternative to traditional artificial neural networks (ANNs) due to their spike-driven paradigm. However, recent research in the SNN domain has mainly ...

Imagine watching a speaker and another person nearby is loudly crunching from a bag of chips. To deal with this, a person ...

Many conventional computer architectures are ill-equipped to meet the computational demands of machine learning-based models. In recent years, some engineers have thus been trying to design ...

Researchers have developed a geometric deep learning approach to uncover shared brain activity patterns across individuals.

Neural networks have revolutionized the fields of artificial intelligence (AI) and machine learning by providing a flexible, and scalable, means to solve complex, and traditionally computationally ...