2 papers
cs.LG2024
A Survey of Deep Graph Learning under Distribution Shifts: from Graph Out-of-Distribution Generalization to Adaptation
Kexin Zhang, Shuhan Liu, Song Wang +6
Distribution shifts on graphs -- the discrepancies in data distribution between training and employing a graph machine learning model -- are ubiquitous and often unavoidable in rea…
cs.LG2024
Beyond Generalization: A Survey of Out-Of-Distribution Adaptation on Graphs
Shuhan Liu, Kaize Ding
Distribution shifts on graphs -- the data distribution discrepancies between training and testing a graph machine learning model, are often ubiquitous and unavoidable in real-world…