{"id":"https://openalex.org/W3137006678","doi":"https://doi.org/10.1109/tbdata.2021.3066151","title":"High-Ratio Lossy Compression: Exploring the Autoencoder to Compress Scientific Data","display_name":"High-Ratio Lossy Compression: Exploring the Autoencoder to Compress Scientific Data","publication_year":2021,"publication_date":"2021-03-17","ids":{"openalex":"https://openalex.org/W3137006678","doi":"https://doi.org/10.1109/tbdata.2021.3066151","mag":"3137006678"},"language":"en","primary_location":{"id":"doi:10.1109/tbdata.2021.3066151","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2021.3066151","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Big Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100392678","display_name":"Tong Liu","orcid":"https://orcid.org/0000-0002-9582-3127"},"institutions":[{"id":"https://openalex.org/I84392919","display_name":"Temple University","ror":"https://ror.org/00kx1jb78","country_code":"US","type":"education","lineage":["https://openalex.org/I84392919"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Tong Liu","raw_affiliation_strings":["Department of Computer and Information Sciences, Temple University, Philadelphia, PA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer and Information Sciences, Temple University, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I84392919"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084396846","display_name":"Jinzhen Wang","orcid":"https://orcid.org/0000-0001-6317-2940"},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jinzhen Wang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, USA","institution_ids":["https://openalex.org/I118118575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100345219","display_name":"Qing Liu","orcid":"https://orcid.org/0000-0002-7600-7976"},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qing Liu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, USA","institution_ids":["https://openalex.org/I118118575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042860328","display_name":"Shakeel Alibhai","orcid":null},"institutions":[{"id":"https://openalex.org/I84392919","display_name":"Temple University","ror":"https://ror.org/00kx1jb78","country_code":"US","type":"education","lineage":["https://openalex.org/I84392919"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shakeel Alibhai","raw_affiliation_strings":["Department of Computer and Information Sciences, Temple University, Philadelphia, PA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer and Information Sciences, Temple University, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I84392919"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101463329","display_name":"Tao L\u00fc","orcid":"https://orcid.org/0000-0003-2362-2446"},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tao Lu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, USA","institution_ids":["https://openalex.org/I118118575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087956045","display_name":"Xubin He","orcid":"https://orcid.org/0000-0002-5071-2861"},"institutions":[{"id":"https://openalex.org/I84392919","display_name":"Temple University","ror":"https://ror.org/00kx1jb78","country_code":"US","type":"education","lineage":["https://openalex.org/I84392919"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xubin He","raw_affiliation_strings":["Department of Computer and Information Sciences, Temple University, Philadelphia, PA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer and Information Sciences, Temple University, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I84392919"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100392678"],"corresponding_institution_ids":["https://openalex.org/I84392919"],"apc_list":null,"apc_paid":null,"fwci":7.8417,"has_fulltext":false,"cited_by_count":74,"citation_normalized_percentile":{"value":0.97626222,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":"9","issue":"1","first_page":"22","last_page":"36"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11181","display_name":"Advanced Data Storage Technologies","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11181","display_name":"Advanced Data Storage Technologies","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11269","display_name":"Algorithms and Data Compression","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.9288266897201538},{"id":"https://openalex.org/keywords/lossy-compression","display_name":"Lossy compression","score":0.90398108959198},{"id":"https://openalex.org/keywords/lossless-compression","display_name":"Lossless compression","score":0.8270035982131958},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8130205869674683},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.6180282831192017},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.5430216193199158},{"id":"https://openalex.org/keywords/compression-ratio","display_name":"Compression ratio","score":0.5287820100784302},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.5116077065467834},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.4999067783355713},{"id":"https://openalex.org/keywords/floating-point","display_name":"Floating point","score":0.49143826961517334},{"id":"https://openalex.org/keywords/compression","display_name":"Compression (physics)","score":0.4813609719276428},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.45407071709632874},{"id":"https://openalex.org/keywords/data-reduction","display_name":"Data reduction","score":0.42085155844688416},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.4191902279853821},{"id":"https://openalex.org/keywords/data-compression-ratio","display_name":"Data compression ratio","score":0.41807496547698975},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.416191041469574},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.409860759973526},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.40467172861099243},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38760772347450256},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3732668161392212},{"id":"https://openalex.org/keywords/image-compression","display_name":"Image compression","score":0.30008798837661743},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2937864363193512},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.08110800385475159},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.0729181170463562}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.9288266897201538},{"id":"https://openalex.org/C165021410","wikidata":"https://www.wikidata.org/wiki/Q55564","display_name":"Lossy compression","level":2,"score":0.90398108959198},{"id":"https://openalex.org/C81081738","wikidata":"https://www.wikidata.org/wiki/Q55542","display_name":"Lossless compression","level":3,"score":0.8270035982131958},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8130205869674683},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.6180282831192017},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.5430216193199158},{"id":"https://openalex.org/C25797200","wikidata":"https://www.wikidata.org/wiki/Q828137","display_name":"Compression ratio","level":3,"score":0.5287820100784302},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.5116077065467834},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4999067783355713},{"id":"https://openalex.org/C84211073","wikidata":"https://www.wikidata.org/wiki/Q117879","display_name":"Floating point","level":2,"score":0.49143826961517334},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.4813609719276428},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.45407071709632874},{"id":"https://openalex.org/C153914771","wikidata":"https://www.wikidata.org/wiki/Q5227343","display_name":"Data reduction","level":2,"score":0.42085155844688416},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.4191902279853821},{"id":"https://openalex.org/C94835093","wikidata":"https://www.wikidata.org/wiki/Q3113333","display_name":"Data compression ratio","level":5,"score":0.41807496547698975},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.416191041469574},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.409860759973526},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.40467172861099243},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38760772347450256},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3732668161392212},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.30008798837661743},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2937864363193512},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.08110800385475159},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.0729181170463562},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C511840579","wikidata":"https://www.wikidata.org/wiki/Q12757","display_name":"Internal combustion engine","level":2,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tbdata.2021.3066151","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2021.3066151","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Big Data","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4951327001","display_name":null,"funder_award_id":"NSF-1828363","funder_id":"https://openalex.org/F4320335353","funder_display_name":"National Science Foundation of Sri Lanka"},{"id":"https://openalex.org/G5389568467","display_name":null,"funder_award_id":"NSF-1813081","funder_id":"https://openalex.org/F4320335353","funder_display_name":"National Science Foundation of Sri Lanka"},{"id":"https://openalex.org/G5931250574","display_name":null,"funder_award_id":"CCF-1718297","funder_id":"https://openalex.org/F4320335353","funder_display_name":"National Science Foundation of Sri Lanka"},{"id":"https://openalex.org/G8798673035","display_name":null,"funder_award_id":"CCF-1812861","funder_id":"https://openalex.org/F4320335353","funder_display_name":"National Science Foundation of Sri Lanka"}],"funders":[{"id":"https://openalex.org/F4320335353","display_name":"National Science Foundation of Sri Lanka","ror":"https://ror.org/010xaa060"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W118291038","https://openalex.org/W1484070046","https://openalex.org/W1589753008","https://openalex.org/W1823244711","https://openalex.org/W2013640190","https://openalex.org/W2035026907","https://openalex.org/W2046288017","https://openalex.org/W2048266589","https://openalex.org/W2052440657","https://openalex.org/W2060038468","https://openalex.org/W2079152413","https://openalex.org/W2109722477","https://openalex.org/W2110455446","https://openalex.org/W2115907784","https://openalex.org/W2120432001","https://openalex.org/W2125800352","https://openalex.org/W2140196014","https://openalex.org/W2146395539","https://openalex.org/W2163496585","https://openalex.org/W2253855427","https://openalex.org/W2475932436","https://openalex.org/W2486202470","https://openalex.org/W2562234976","https://openalex.org/W2625759119","https://openalex.org/W2739870291","https://openalex.org/W2752881958","https://openalex.org/W2755132285","https://openalex.org/W2756631316","https://openalex.org/W2886627854","https://openalex.org/W2899412261","https://openalex.org/W2964219139","https://openalex.org/W2971247417","https://openalex.org/W2971854097","https://openalex.org/W2973204506","https://openalex.org/W2978021548","https://openalex.org/W2982580815","https://openalex.org/W2999752146","https://openalex.org/W3006642836","https://openalex.org/W3043058721","https://openalex.org/W4230077428","https://openalex.org/W4294567867","https://openalex.org/W6630236247","https://openalex.org/W6635226153","https://openalex.org/W6734035190"],"related_works":["https://openalex.org/W2993349805","https://openalex.org/W2207317090","https://openalex.org/W4381744720","https://openalex.org/W4287393224","https://openalex.org/W3118996461","https://openalex.org/W2541319825","https://openalex.org/W1990134912","https://openalex.org/W2088378984","https://openalex.org/W3080614128","https://openalex.org/W4200061735"],"abstract_inverted_index":{"Scientific":[0],"simulations":[1],"on":[2,104,122,137],"high-performance":[3],"computing":[4],"(HPC)":[5],"systems":[6],"can":[7,48,100,215],"generate":[8],"large":[9],"amounts":[10],"of":[11,58,65,70,125,184],"floating-point":[12,31,152],"data":[13,19,25,50,91,131,142],"per":[14],"run.":[15],"To":[16],"mitigate":[17],"the":[18,24,56,59,78,83,98,115,123,158,185,188],"storage":[20],"bottleneck":[21],"and":[22,46,132,173,197,209],"lower":[23],"volume,":[26],"it":[27],"is":[28,72,108],"common":[29],"for":[30,90,114,140,182,219],"compressors":[32],"to":[33,38,127,150,162,168,195,201,222],"be":[34,163],"employed.":[35],"As":[36],"compared":[37],"lossless":[39],"compressors,":[40,42],"lossy":[41],"such":[43],"as":[44],"SZ":[45,192],"ZFP,":[47],"reduce":[49,151],"volume":[51],"more":[52,66],"aggressively":[53],"while":[54],"maintaining":[55],"usefulness":[57],"data.":[60,79,153,225],"However,":[61],"a":[62,119],"reduction":[63],"ratio":[64],"than":[67],"two":[68],"orders":[69],"magnitude":[71],"almost":[73],"impossible":[74],"without":[75],"seriously":[76],"distorting":[77],"In":[80,110],"deep":[81],"learning,":[82],"autoencoder":[84,99,190],"technique":[85],"has":[86],"shown":[87],"great":[88],"potential":[89],"compression,":[92],"in":[93,166,203,212],"particular":[94],"with":[95],"images.":[96],"Whether":[97],"deliver":[101],"similar":[102],"performance":[103],"scientific":[105,130,141,224],"data,":[106],"however,":[107],"unknown.":[109],"this":[111,213],"article,":[112],"we":[113],"first":[116],"time":[117],"conduct":[118],"comprehensive":[120],"study":[121,155],"use":[124],"autoencoders":[126,139,221],"compress":[128,223],"real-world":[129],"illustrate":[133],"several":[134],"key":[135],"findings":[136],"using":[138,220],"reduction.":[143],"We":[144],"implement":[145],"an":[146],"autoencoder-based":[147],"compression":[148,171,204],"prototype":[149],"Our":[154,177,207],"shows":[156],"that":[157],"out-of-the-box":[159],"implementation":[160],"needs":[161],"further":[164],"tuned":[165,189],"order":[167],"achieve":[169],"high":[170],"ratios":[172],"satisfactory":[174],"error":[175],"bounds.":[176],"evaluation":[178],"results":[179],"show":[180],"that,":[181],"most":[183],"test":[186],"datasets,":[187],"outperforms":[191],"by":[193,199],"up":[194,200],"4X,":[196],"ZFP":[198],"50X":[202],"ratios,":[205],"respectively.":[206],"practices":[208],"lessons":[210],"learned":[211],"work":[214],"direct":[216],"future":[217],"optimizations":[218]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":22},{"year":2024,"cited_by_count":19},{"year":2023,"cited_by_count":17},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":3}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}
