2 papers
cs.LG2025
Demystifying MPNNs: Message Passing as Merely Efficient Matrix Multiplication
Qin Jiang, Chengjia Wang, Michael Lones +1
While Graph Neural Networks (GNNs) have achieved remarkable success, their design largely relies on empirical intuition rather than theoretical understanding. In this paper, we pre…
cs.LG2024
ScaleNet: Scale Invariance Learning in Directed Graphs
Qin Jiang, Chengjia Wang, Michael Lones +2
Graph Neural Networks (GNNs) have advanced relational data analysis but lack invariance learning techniques common in image classification. In node classification with GNNs, it is…