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cs.LG2026
Can Graph Learning Learn Circuits?
Chester Tan, Moritz Lampert, Courtney Maynard +3
Circuit localization is a mechanistic interpretability task whose goal is to identify a sparse subgraph of a transformer's computation graph sufficient to reproduce a particular be…
cs.LG2024
REGE: A Method for Incorporating Uncertainty in Graph Embeddings
Zohair Shafi, Germans Savcisens, Tina Eliassi-Rad
Machine learning models for graphs in real-world applications are prone to two primary types of uncertainty: (1) those that arise from incomplete and noisy data and (2) those that…
cs.LG2024
Generating Human Understandable Explanations for Node Embeddings
Zohair Shafi, Ayan Chatterjee, Tina Eliassi-Rad
Node embedding algorithms produce low-dimensional latent representations of nodes in a graph. These embeddings are often used for downstream tasks, such as node classification and…