arXiv Machine Learning July 21, 2026 By Kaiyuan Tang, Maizhe Yang, Chaoli Wang

EVOLVE: Efficient Learned Volume Compression with Variable-Rate Encoding on a Cross-Domain Database

Read the original on arXiv Machine Learning →

arXiv:2607. 18187v1 Announce Type: cross Abstract: Large-scale scientific simulations generate volumetric data at rates that far outpace advances in storage and network bandwidth, making effective lossy compression increasingly critical.

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

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