4 papers
Task-Relevant Null-Space Residuals for Non-Injective Neural Mappings
Bizu Feng, Zhimu Yang, Shuming Wang +4
Non-injective mappings in neural networks map distinct inputs to the same representation, thereby implicitly inducing equivalence relations in the input space. However, the input d…
A Polynomial Architecture-Attribution Co-Design Framework for Exact Aumann-Shapley Attribution in GNNs
Bizu Feng, Zhimu Yang, Shuming Wang +4
We study feature-level and node-level explanations for graph neural networks (GNNs) through the lens of Aumann-Shapley attribution. Path-integral methods such as Integrated Gradien…
FSX: Message Flow Sensitivity Enhanced Structural Explainer for Graph Neural Networks
Bizu Feng, Zhimu Yang, Shaode Yu +1
Despite the widespread success of Graph Neural Networks (GNNs), understanding the reasons behind their specific predictions remains challenging. Existing explainability methods fac…
Exploring Kolmogorov-Arnold networks for realistic image sharpness assessment
Shaode Yu, Ze Chen, Zhimu Yang +2
Score prediction is crucial in evaluating realistic image sharpness based on collected informative features. Recently, Kolmogorov-Arnold networks (KANs) have been developed and wit…