AINeutralarXiv – CS AI · 9h ago6/10
🧠
Residual Modeling for High-Fidelity Learned Compression of Scientific Data
Researchers present novel residual-centric compression methods (LBRC and NGLR) for scientific data that improve upon existing learned compression approaches by tailoring the encoding of reconstruction residuals to their structural properties. The techniques achieve 30-60% better compression ratios than Guaranteed Autoencoders and outperform the SZ compressor in high-fidelity regimes, addressing a critical bottleneck in compressing massive spatiotemporal datasets from scientific simulations.