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: Cognitive radio (CR) facilitates efficient spectrum management and optimization in wireless networks with massive wireless access and data transmission demands, where spectrum sensing (SS) ...

This project develops a neural network to predict car fuel efficiency (MPG) using the Auto MPG dataset, featuring data preprocessing, model training with PyTorch, and custom prediction capabilities.

This library provides PyTorch implementations of tensor-train decomposed neural network layers that can significantly reduce the number of parameters in deep neural networks while maintaining accuracy ...

To improve the resilience of the computer network infrastructure against cyber attacks or causal influences and find ways to mitigate their impact, we need to understand their structure and dynamics.