arXiv Machine Learning June 16, 2026 By Fuyan Zhang, Yuqi Li, Yingli Tian, Edmond S. L. Ho

DYNA-PRUNER: Input-Adaptive Data-Model Co-Pruning for Efficient and Scalable Spatio-Temporal Media Prediction

Read the original on arXiv Machine Learning →

arXiv:2606. 15346v1 Announce Type: cross Abstract: Spatio-temporal prediction supports radar/satellite nowcasting and city-scale traffic monitoring, but modern models are often too expensive for real-time deployment.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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