activity
20232026
most citedA Survey on Error-Bounded Lossy Compression for Scientific Datasets

2 citations · 2 across the 14 of their papers we have counts for

collaborators
Showing 2026Show all

8 papers · 1 filter

cs.CV2026

PLEDGE: Progressive Lossy Error-Bounded Compression of 3D Gaussian Splatting

Mingze Xia, Yuxiao Li, Baixi Sun +6

Existing 3D Gaussian Splatting (3DGS) codecs report reconstruction quality after compression, and give users little control over the distortion of individual primitives. We present…

cs.DC2026

FaCTz: Fast Critical-Point and Topology-Aware GPU Compression for Scientific Vector Fields

Mingze Xia, Yuxiao Li, Sheng Di +6

Error-bounded lossy compression is essential for storing and transferring the vector-field data produced by large-scale scientific simulations. Although it enforces a user-specifie…

cs.HC2026

FZ-VIS: A Visual Analytics Framework for Quantities-of-Interest-Aware Scientific Lossy Compression

Guoxi Liu, Yuxiao Li, Congrong Ren +6

Modern scientific simulations generate massive volumes of data, making lossy compression essential for efficient storage and transmission. However, preserving critical quantities o…

cs.LG2026

Preserving Clusters in Error-Bounded Lossy Compression of Scientific Particle Data

Congrong Ren, Sheng Di, Katrin Heitmann +2

Scientific particle simulations in cosmology, molecular dynamics, and fluid dynamics produce large-scale datasets whose storage, movement, and analysis increasingly rely on lossy c…

cs.DC2026

EXaCTz: Guaranteed Extremum Graph and Contour Tree Preservation for Distributed- and GPU-Parallel Lossy Compression

Yuxiao Li, Mingze Xia, Xin Liang +2

This paper introduces EXaCTz, a parallel algorithm that corrects lossy-compressed scalar field data to preserve extremum graphs and contour trees concurrently. While error-bounded…

cs.DC2026

TopoSZp: Lightweight Topology-Aware Error-controlled Compression for Scientific Data

Tripti Agarwal, Sheng Di, Xin Liang +5

Error-bounded lossy compression is essential for managing the massive data volumes produced by large-scale HPC simulations. While state-of-the-art compressors such as SZ and ZFP pr…

cs.DC2026

pMSz: A Distributed Parallel Algorithm for Correcting Extrema and Morse Smale Segmentations in Lossy Compression

Yuxiao Li, Mingze Xia, Xin Liang +7

Lossy compression, widely used by scientists to reduce data from simulations, experiments, and observations, can distort features of interest even under bounded error. Such distort…

cs.DC2026

FFCz: Fast Fourier Correction for Spectrum-Preserving Lossy Compression of Scientific Data

Congrong Ren, Robert Underwood, Sheng Di +5

This paper introduces a novel technique to preserve spectral features in lossy compression based on a novel fast Fourier correction algorithm\added{ for regular-grid data}. Preserv…