Continuous-Time Quantum Walks based Graph Neural Network

arXiv:2603.22365v1 Announce Type: cross Abstract: With the rapid growth of interconnected devices, accurately detecting malicious activities in network traffic has become

arXiv:2604.08553v1 Announce Type: cross Abstract: Large Language Models (LLMs) have shown strong performance on text-attributed graphs (TAGs) due to their superior semantic

<p><em>A build log on QTGNN v2, what happens when the message function in a graph attention network is a variational quantum circuit instead of a matrix multiply.</em></p>

arXiv:2607.21607v1 Announce Type: new Abstract: Graph Neural Networks propagate information through local message passing, but the graph topologies themselves can silently prevent