{"id":"https://openalex.org/W4402353003","doi":"https://doi.org/10.1109/ijcnn60899.2024.10650926","title":"Error Bound Based Noise Schedule Design in Diffusion Models","display_name":"Error Bound Based Noise Schedule Design in Diffusion Models","publication_year":2024,"publication_date":"2024-06-30","ids":{"openalex":"https://openalex.org/W4402353003","doi":"https://doi.org/10.1109/ijcnn60899.2024.10650926"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn60899.2024.10650926","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn60899.2024.10650926","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-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/A5100657035","display_name":"Liyuan Liu","orcid":"https://orcid.org/0000-0003-2585-323X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Liyuan Liu","raw_affiliation_strings":["Tsinghua University,Shenzhen International Graduate School,Shenzhen,China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Shenzhen International Graduate School,Shenzhen,China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101456902","display_name":"Chun Yuan","orcid":"https://orcid.org/0000-0002-3590-6676"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chun Yuan","raw_affiliation_strings":["Tsinghua University,Shenzhen International Graduate School,Shenzhen,China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Shenzhen International Graduate School,Shenzhen,China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100657035"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14619197,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"37","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10928","display_name":"Probabilistic and Robust Engineering Design","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10928","display_name":"Probabilistic and Robust Engineering Design","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9922000169754028,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6577810645103455},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5694470405578613},{"id":"https://openalex.org/keywords/schedule","display_name":"Schedule","score":0.5463661551475525},{"id":"https://openalex.org/keywords/diffusion","display_name":"Diffusion","score":0.5058786273002625},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.4271542429924011},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.18049356341362},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13036823272705078},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.09286335110664368}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6577810645103455},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5694470405578613},{"id":"https://openalex.org/C68387754","wikidata":"https://www.wikidata.org/wiki/Q7271585","display_name":"Schedule","level":2,"score":0.5463661551475525},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.5058786273002625},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.4271542429924011},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.18049356341362},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13036823272705078},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.09286335110664368},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn60899.2024.10650926","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn60899.2024.10650926","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1505878979","https://openalex.org/W1663973292","https://openalex.org/W1991111872","https://openalex.org/W2013035813","https://openalex.org/W2959300817","https://openalex.org/W3003301247","https://openalex.org/W3004970274","https://openalex.org/W3034600949","https://openalex.org/W3036167779","https://openalex.org/W3208015123","https://openalex.org/W3213234378","https://openalex.org/W4281661987","https://openalex.org/W4281690218","https://openalex.org/W4281969232","https://openalex.org/W4287121833","https://openalex.org/W4301206121","https://openalex.org/W4303440777","https://openalex.org/W4310695675","https://openalex.org/W4312388283","https://openalex.org/W4312933868","https://openalex.org/W4313142698","https://openalex.org/W4320343052","https://openalex.org/W4390873030","https://openalex.org/W6679045638","https://openalex.org/W6765775151","https://openalex.org/W6765779288","https://openalex.org/W6779823529","https://openalex.org/W6783182287","https://openalex.org/W6783713337","https://openalex.org/W6786375611","https://openalex.org/W6788990321","https://openalex.org/W6795986329","https://openalex.org/W6796588791","https://openalex.org/W6802422826","https://openalex.org/W6809884996","https://openalex.org/W6810793953","https://openalex.org/W6811291704","https://openalex.org/W6838327568","https://openalex.org/W6838452192","https://openalex.org/W6838815585","https://openalex.org/W6844305113","https://openalex.org/W6845281891","https://openalex.org/W6846176957","https://openalex.org/W6847293244","https://openalex.org/W6849671399","https://openalex.org/W6849745102"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W2382290278","https://openalex.org/W4395014643"],"abstract_inverted_index":{"Diffusion-based":[0],"generative":[1,8],"model":[2,173],"currently":[3],"serves":[4],"as":[5,24],"a":[6,14,75],"mainstream":[7],"method.":[9,162],"The":[10],"noise":[11,44,52,83,110,135,146,167],"schedule":[12,53,84,111,136,147,168],"has":[13],"significant":[15],"impact":[16],"on":[17,140,154],"the":[18,28,31,36,39,51,55,59,65,86,96,113,117,124,171,176],"training":[19,33,73,181],"process":[20],"of":[21,30,38,57,64,89,115,120,127,152],"diffusion":[22],"model,":[23],"it":[25],"affects":[26],"both":[27],"distribution":[29],"noisy":[32],"set":[34],"and":[35,85,101,143],"weights":[37],"objective":[40],"function":[41],"at":[42,179],"each":[43],"level.":[45],"In":[46],"this":[47],"paper,":[48],"we":[49,78,94],"design":[50,108],"from":[54,74],"scope":[56],"reducing":[58,116],"final":[60,102],"error":[61,103,121],"upper":[62,87,118],"bound":[63,88,119],"reverse":[66,105],"denoising":[67],"process.":[68,106],"By":[69],"examining":[70],"Monte":[71],"Carlo":[72],"theoretical":[76],"perspective,":[77],"establish":[79],"an":[80],"association":[81],"between":[82,98],"network":[90,99,128],"output":[91,100],"error.":[92],"Furthermore,":[93],"derive":[95],"connection":[97],"through":[104],"We":[107],"our":[109,134,166],"with":[112,123],"goal":[114],"combined":[122],"correlation":[125],"analysis":[126],"output.":[129],"Experimental":[130],"results":[131],"demonstrate":[132],"that":[133],"enhances":[137],"perceptual":[138],"quality":[139,178],"CIFAR-10,":[141],"FFHQ-64x64":[142],"AFHQv2-64x64.":[144],"Our":[145],"achieves":[148],"state-of-the-art":[149],"FID":[150],"score":[151],"1.70":[153],"CIFAR-10":[155],"unconditional":[156],"generation":[157],"task":[158],"using":[159,165],"discriminator":[160],"guidance":[161],"On":[163],"FFHQ/AFHQv2,":[164],"to":[169],"retrain":[170],"pre-trained":[172],"can":[174],"improve":[175],"sample":[177],"little":[180],"cost.":[182]},"counts_by_year":[],"updated_date":"2025-12-19T19:40:27.379048","created_date":"2025-10-10T00:00:00"}
