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multivariate-event-streams

topic1 events
papersSEP 10 04:00 UTC

SurF: A Generative Model for Multivariate Irregular Time Series Forecasting

Researchers introduce SurF, a generative model designed for multivariate event streams that are sampled at irregular intervals. The work argues that tokenization-based approaches struggle when the gaps between events span orders of magnitude, and proposes an alternative suited to such data. The paper is a revised arXiv submission in machine learning.

time-series/generative-models/arxiv/forecasting