{"id":"https://openalex.org/W7160394561","doi":"https://doi.org/10.48550/arxiv.2605.04013","title":"Conditional Diffusion Sampling","display_name":"Conditional Diffusion Sampling","publication_year":2026,"publication_date":"2026-05-05","ids":{"openalex":"https://openalex.org/W7160394561","doi":"https://doi.org/10.48550/arxiv.2605.04013"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.04013","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.04013","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.04013","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5092503857","display_name":"Francisco M. Castro-Mac\u00edas","orcid":"https://orcid.org/0000-0002-9040-3641"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Castro-Mac\u00edas, Francisco M.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135453660","display_name":"Pablo Morales-\u00c1lvarez","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Morales-\u00c1lvarez, Pablo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003160514","display_name":"Saifuddin Syed","orcid":"https://orcid.org/0000-0002-8499-8255"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Syed, Saifuddin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135522615","display_name":"Daniel Hern\u00e1ndez-Lobato","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hern\u00e1ndez-Lobato, Daniel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023830568","display_name":"Rafael Molina","orcid":"https://orcid.org/0000-0003-4694-8588"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Molina, Rafael","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135503067","display_name":"Jos\u00e9 Miguel Hern\u00e1ndez-Lobato","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hern\u00e1ndez-Lobato, Jos\u00e9 Miguel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11304","display_name":"Advanced Neuroimaging Techniques and Applications","score":0.4311000108718872,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11304","display_name":"Advanced Neuroimaging Techniques and Applications","score":0.4311000108718872,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.13529999554157257,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10241","display_name":"Functional Brain Connectivity Studies","score":0.0632999986410141,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.8007000088691711},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.6628000140190125},{"id":"https://openalex.org/keywords/stochastic-differential-equation","display_name":"Stochastic differential equation","score":0.6089000105857849},{"id":"https://openalex.org/keywords/importance-sampling","display_name":"Importance sampling","score":0.5060999989509583},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.4896000027656555},{"id":"https://openalex.org/keywords/diffusion","display_name":"Diffusion","score":0.4677000045776367},{"id":"https://openalex.org/keywords/conditional-probability-distribution","display_name":"Conditional probability distribution","score":0.35199999809265137},{"id":"https://openalex.org/keywords/stochastic-process","display_name":"Stochastic process","score":0.3386000096797943}],"concepts":[{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.8007000088691711},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.6628000140190125},{"id":"https://openalex.org/C51955184","wikidata":"https://www.wikidata.org/wiki/Q1545585","display_name":"Stochastic differential equation","level":2,"score":0.6089000105857849},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5884000062942505},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.5060999989509583},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4896000027656555},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.4677000045776367},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4569000005722046},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3928000032901764},{"id":"https://openalex.org/C43555835","wikidata":"https://www.wikidata.org/wiki/Q2300258","display_name":"Conditional probability distribution","level":2,"score":0.35199999809265137},{"id":"https://openalex.org/C8272713","wikidata":"https://www.wikidata.org/wiki/Q176737","display_name":"Stochastic process","level":2,"score":0.3386000096797943},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3271999955177307},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.310699999332428},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30979999899864197},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.2935999929904938},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.29100000858306885},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.2797999978065491},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.27379998564720154},{"id":"https://openalex.org/C93226319","wikidata":"https://www.wikidata.org/wiki/Q193137","display_name":"Differential (mechanical device)","level":2,"score":0.2669999897480011},{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.2667999863624573},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.2667999863624573},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.263700008392334},{"id":"https://openalex.org/C20326153","wikidata":"https://www.wikidata.org/wiki/Q7049638","display_name":"Nonuniform sampling","level":3,"score":0.25870001316070557},{"id":"https://openalex.org/C189508267","wikidata":"https://www.wikidata.org/wiki/Q17088227","display_name":"Density estimation","level":3,"score":0.2526000142097473}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.04013","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.04013","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.04013","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.04013","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Sampling":[0,61],"from":[1,104],"unnormalized":[2],"multimodal":[3],"distributions":[4],"with":[5,163],"limited":[6],"density":[7,183],"evaluations":[8],"remains":[9],"a":[10,22,25,45,63,77,105,131,176],"fundamental":[11],"challenge":[12],"in":[13],"machine":[14],"learning":[15],"and":[16,28,113,144,182],"natural":[17],"sciences.":[18],"Successful":[19],"approaches":[20,43],"construct":[21],"bridge":[23],"between":[24,179],"tractable":[26],"reference":[27],"the":[29,37,49,116,141,151,157,172],"target":[30],"distribution.":[31],"Parallel":[32],"Tempering":[33],"(PT)":[34],"serves":[35],"as":[36],"gold":[38],"standard,":[39],"while":[40],"recent":[41],"diffusion-based":[42],"offer":[44],"continuous":[46],"alternative":[47],"at":[48],"cost":[50,117,185],"of":[51,79,118,161],"neural":[52,97],"training.":[53],"In":[54],"this":[55,71,119,129],"work,":[56],"we":[57,73,109],"introduce":[58],"Conditional":[59,75],"Diffusion":[60],"(CDS),":[62],"framework":[64],"that":[65,115,169],"combines":[66],"these":[67,100],"two":[68],"paradigms.":[69],"To":[70],"end,":[72],"derive":[74],"Interpolants,":[76],"class":[78],"stochastic":[80,91],"processes":[81],"whose":[82],"transport":[83,152],"dynamics":[84,101],"are":[85,148],"governed":[86],"by":[87,130],"an":[88],"exact,":[89],"closed-form":[90],"differential":[92],"equation":[93],"(SDE),":[94],"requiring":[95],"no":[96],"approximation.":[98],"Although":[99],"require":[102],"sampling":[103],"non-trivial":[106],"initialization":[107,120],"distribution,":[108,143],"show":[110],"both":[111],"theoretically":[112],"empirically":[114],"diminishes":[121],"for":[122],"sufficiently":[123],"short":[124],"diffusion":[125],"times.":[126],"CDS":[127,170],"leverages":[128],"two-stage":[132],"procedure:":[133],"(1)":[134],"PT":[135,162],"is":[136],"used":[137],"to":[138,174,187],"efficiently":[139],"sample":[140,180],"initial":[142],"then":[145],"(2)":[146],"samples":[147],"transported":[149],"via":[150],"SDE.":[153],"This":[154],"combination":[155],"couples":[156],"robust":[158],"global":[159],"exploration":[160],"efficient":[164],"local":[165],"transport.":[166],"Experiments":[167],"suggest":[168],"has":[171],"potential":[173],"achieve":[175],"superior":[177],"trade-off":[178],"quality":[181],"evaluation":[184],"compared":[186],"state-of-the-art":[188],"samplers.":[189]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-07T00:00:00"}