Author

A. Rangarajan

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#machine learning Preprint Sep 2026

Neural Residual Modeling for Scientific Data Compression under Guaranteed Error Bounds

This work proposes a post-processing pipeline that augments an RVQ-based compressor with a U-Net trained to predict and correct pixel-space residuals between the original volume and its RVQ reconstruction, and is the first pipeline to combine latent-space RVQ, explicit pixel-space residual correction via a deep spatial...

Surya Majumder, Liang-Ji Zhu, Sanjay Ranka et al. · 0 citations

#machine learning Preprint Aug 2026

Multivariate Scientific Data Compression with Learned Cross-Variable Latent Decorrelation and Autoregressive Entropy Modeling

CAESAR-LDAR is presented, an error-controlled multivariate learned compressor that augments a shared CAESAR-V backbone with two complementary mechanisms: a trainable orthogonal transform that reorganizes dependence across aligned latent channels, and a causal autoregressive hierarchical prior that captures local spatia...

Liang-Ji Zhu, A. Rangarajan, Sanjay Ranka · 0 citations