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arXiv Machine Learning By Alexander Panyshev, Dmitry Vinichenko, Oleg Travkin, Roman Alferov, Alexey Zaytsev

Never Skip a Batch: Dense Learning of Temporal GNNs via Adaptive Pseudo-Supervision

Read the original on arXiv Machine Learning →

arXiv:2505. 12526v2 Announce Type: replace Abstract: Temporal graph networks suffer from irregular supervision in realworld dynamic graphs, as most minibatches contain few labeled events.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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