2 papers
cs.LG2026
A Fair Evaluation of Graph Foundation Models for Node Property Prediction
Oleg Platonov, Gleb Bazhenov, Dmitry Eremeev +1
Due to the wide use of graph-structured data in different fields of industry and science, the development of Graph Foundation Models (GFMs) has recently attracted a lot of attentio…
cs.LG2026
Heat and Matérn Kernels on Matchings
Dmitry Eremeev, Salem Said, Viacheslav Borovitskiy
Applying kernel methods to matchings is challenging due to their discrete, non-Euclidean nature. In this paper, we develop a principled framework for constructing geometric kernels…