Detection of LFM signals in low SNR based on STFT and wavelet denoising. - Yu Duan; Jinzhen Wang; Shaoying Su; Zengping Chen (ICAILP, 2014)

Accurate parameters estimation of chirp signal in low SNR. - Jinzhen Wang; Shaoying Su; Zengping Chen (ICAILP, 2014)

Parameter estimation of chirp signal under low SNR. - Jinzhen Wang; Shaoying Su; Zengping Chen (Sci. China Inf. Sci., 2015)

Research of Recognition System of Web Intrusion Detection Based on Storm. - Bo Li 123; Jinzhen Wang; Ping Zhao; Zhongjiang Yan; Mao Yang 001 (ICNCC, 2016)

SIRIUS: Enabling Progressive Data Exploration for Extreme-Scale Scientific Data. - Zhenbo Qiao; Tao Lu; Huizhang Luo; Qing Liu 002; Scott Klasky; Norbert Podhorszki; Jinzhen Wang (IEEE Trans. Multi Scale Comput. Syst., 2018)

Identifying Latent Reduced Models to Precondition Lossy Compression. - Huizhang Luo; Dan Huang 001; Qing Liu 002; Zhenbo Qiao; Hong Jiang 001; Jing Bi 001; Haitao Yuan 001; Mengchu Zhou; Jinzhen Wang; Zhenlu Qin (IPDPS, 2019)

Exploring Transfer Learning to Reduce Training Overhead of HPC Data in Machine Learning. - Tong Liu; Shakeel Alibhai; Jinzhen Wang; Qing Liu 002; Xubin He; Chentao Wu (NAS, 2019)

Compression Ratio Modeling and Estimation across Error Bounds for Lossy Compression. - Jinzhen Wang; Tong Liu; Qing Liu 002; Xubin He; Huizhang Luo; Weiming He (IEEE Trans. Parallel Distributed Syst., 2020)

Reducing the Training Overhead of the HPC Compression Autoencoder via Dataset Proportioning. - Tong Liu; Shakeel Alibhai; Jinzhen Wang; Qing Liu 002; Xubin He (NAS, 2021)

Unbalanced Parallel I/O: An Often-Neglected Side Effect of Lossy Scientific Data Compression. - Xinying Wang 001; Lipeng Wan 001; Jieyang Chen; Qian Gong; Ben Whitney; Jinzhen Wang; Ana Gainaru; Qing Liu 002; Norbert Podhorszki; Dongfang Zhao 001; Feng Yan 001; Scott Klasky (DRBSD@SC, 2021)

Analyzing the Impact of Lossy Data Reduction on Volume Rendering of Cosmology Data. - Jinzhen Wang; Pascal Grosset; Terece L. Turton; James P. Ahrens (DRBSD@SC, 2022)

Locality-based transfer learning on compression autoencoder for efficient scientific data lossy compression. - Nan Wang; Tong Liu; Jinzhen Wang; Qing Liu 002; Shakeel Alibhai; Xubin He (J. Netw. Comput. Appl., 2022)

Improving Progressive Retrieval for HPC Scientific Data using Deep Neural Network. - Jinzhen Wang; Xin Liang 001; Ben Whitney; Jieyang Chen; Qian Gong; Xubin He; Lipeng Wan 001; Scott Klasky; Norbert Podhorszki; Qing Liu 002 (ICDE, 2023)

High-Ratio Lossy Compression: Exploring the Autoencoder to Compress Scientific Data. - Tong Liu; Jinzhen Wang; Qing Liu 002; Shakeel Alibhai; Tao Lu; Xubin He (IEEE Trans. Big Data, 2023)

zPerf: A Statistical Gray-Box Approach to Performance Modeling and Extrapolation for Scientific Lossy Compression. - Jinzhen Wang; Qi Chen; Tong Liu; Qing Liu 002; Xubin He (IEEE Trans. Computers, 2023)

QualityNet: Error-bounded Lossy Compression Quality Prediction via Deep Surrogate. - Khondoker Mirazul Mumenin; Dong Dai 001; Jinzhen Wang; Sheng Di (IEEE Big Data, 2024)

A Generic Performance Metric for Scientific Data Compression. - Zhenlu Qin; Jessie Gu; Maggie Liu; Jinzhen Wang; Hongjian Zhu (e-Science, 2024)

GWLZ: A Group-wise Learning-based Lossy Compression Framework for Scientific Data. - Wenqi Jia 003; Sian Jin; Jinzhen Wang; Wei Niu 002; Dingwen Tao; Miao Yin (FlexScience@HPDC, 2024)

Tango: A Cross-layer Approach to Managing I/O Interference over Local Ephemeral Storage. - Zhenbo Qiao; Qirui Tian; Zhenlu Qin; Jinzhen Wang; Qing Liu 002; Norbert Podhorszki; Scott Klasky; Hongjian Zhu (SC, 2024)

NeurLZ: On Enhancing Lossy Compression Performance based on Error-Controlled Neural Learning for Scientific Data. - Wenqi Jia 003; Youyuan Liu; Zhewen Hu; Jinzhen Wang; Boyuan Zhang; Wei Niu 002; Junzhou Huang; Stavros Kalafatis; Sian Jin; Miao Yin (CoRR, 2024)