Author

S. Kurashkin

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Open access Jul 2026

Is There a Best Hypergraph Neural Network? A Significance-Aware Recomputation and Statistical Audit of DHG-Bench

Deep hypergraph learning is evaluated almost entirely through leaderboards that rank methods by mean accuracy over a few random seeds, usually without significance testing. Is there a best hypergraph neural network, or does the apparent ordering reflect seed noise? We independently recomputed the node-classification tr...

V. Tynchenko, S. Kurashkin, Alexey S. Borodulin et al. · Machine Learning and Knowled... · 0 citations

Review Open access Aug 2026

The Current Generation of Tabular Foundation Models: A Critical Review

This review is, to the authors' knowledge, the first organised around the current generation of tabular foundation models, and taxonomises the architectures by pretraining regime, maps the capability space across five axes, isolates the language-model-on-tabular strand for prediction, feature engineering and generation...

S. Kurashkin, V. Tynchenko, Alexey S. Borodulin et al. · Machine Learning and Knowled... · 1 citation