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Residual Modeling for High-Fidelity Learned Compression of Scientific Data

Liangji Zhu, Sanjay Ranka, Anand Rangarajan
Jun 5, 2026 at 04:00
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arXiv:2606.05389v1 Announce Type: new Abstract: Lossy compression is essential for massive spatiotemporal data from scientific simulations. Learned compressors can achieve high compression ratios at moderate accuracy targets, but their aggregate reconstruction losses do not guarantee accuracy for each block. Existing Guaranteed Autoencoder (GAE)...

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