{"id":"https://openalex.org/W7154331287","doi":"https://doi.org/10.48550/arxiv.2604.10672","title":"One-Step Score-Based Density Ratio Estimation","display_name":"One-Step Score-Based Density Ratio Estimation","publication_year":2026,"publication_date":"2026-04-12","ids":{"openalex":"https://openalex.org/W7154331287","doi":"https://doi.org/10.48550/arxiv.2604.10672"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.10672","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.10672","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.2604.10672","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133559287","display_name":"Wei Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Chen, Wei","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133564337","display_name":"Qibin Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Qibin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133592847","display_name":"John Paisley","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Paisley, John","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133561115","display_name":"Junmei Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Junmei","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5024747577","display_name":"Delu Zeng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zeng, Delu","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5133559287"],"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.32659998536109924,"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"}},"topics":[{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.32659998536109924,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.11069999635219574,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.094200000166893,"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/inference","display_name":"Inference","score":0.6499999761581421},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.5605999827384949},{"id":"https://openalex.org/keywords/probability-density-function","display_name":"Probability density function","score":0.5601999759674072},{"id":"https://openalex.org/keywords/density-estimation","display_name":"Density estimation","score":0.486299991607666},{"id":"https://openalex.org/keywords/basis","display_name":"Basis (linear algebra)","score":0.4189000129699707},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4189000129699707},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.35199999809265137},{"id":"https://openalex.org/keywords/mutual-information","display_name":"Mutual information","score":0.34860000014305115},{"id":"https://openalex.org/keywords/function-approximation","display_name":"Function approximation","score":0.33649998903274536}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6499999761581421},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.5605999827384949},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.5601999759674072},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5246999859809875},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.49570000171661377},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4943999946117401},{"id":"https://openalex.org/C189508267","wikidata":"https://www.wikidata.org/wiki/Q17088227","display_name":"Density estimation","level":3,"score":0.486299991607666},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.44269999861717224},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.4189000129699707},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4189000129699707},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.38420000672340393},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.35199999809265137},{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.34860000014305115},{"id":"https://openalex.org/C91873725","wikidata":"https://www.wikidata.org/wiki/Q3445816","display_name":"Function approximation","level":3,"score":0.33649998903274536},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.3343000113964081},{"id":"https://openalex.org/C5917680","wikidata":"https://www.wikidata.org/wiki/Q2621825","display_name":"Basis function","level":2,"score":0.32179999351501465},{"id":"https://openalex.org/C145242015","wikidata":"https://www.wikidata.org/wiki/Q774123","display_name":"Approximation theory","level":2,"score":0.3149000108242035},{"id":"https://openalex.org/C2777472644","wikidata":"https://www.wikidata.org/wiki/Q16968992","display_name":"Approximate inference","level":3,"score":0.31369999051094055},{"id":"https://openalex.org/C122383733","wikidata":"https://www.wikidata.org/wiki/Q865920","display_name":"Approximation error","level":2,"score":0.31290000677108765},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3100999891757965},{"id":"https://openalex.org/C205979905","wikidata":"https://www.wikidata.org/wiki/Q215084","display_name":"Analytic function","level":2,"score":0.3050000071525574},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.27720001339912415},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.27709999680519104},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.2770000100135803},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.27129998803138733},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.2533000111579895},{"id":"https://openalex.org/C65660741","wikidata":"https://www.wikidata.org/wiki/Q3952743","display_name":"Score","level":2,"score":0.2506999969482422}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.10672","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.10672","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.2604.10672","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.10672","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Density":[0,78],"ratio":[1],"estimation":[2,22,194],"(DRE)":[3],"is":[4,48],"a":[5,19,82,124,190],"useful":[6],"tool":[7],"for":[8,132,148,157],"quantifying":[9],"discrepancies":[10],"between":[11,21,46,193],"probability":[12],"distributions,":[13],"but":[14,63],"existing":[15,169],"approaches":[16],"often":[17,55],"involve":[18],"trade-off":[20],"quality":[23,195],"and":[24,71,85,101,135,152,160,178,182,196],"computational":[25],"efficiency.":[26,198],"Classical":[27],"direct":[28],"DRE":[29,53,137],"methods":[30,54],"are":[31],"usually":[32],"efficient":[33],"at":[34],"inference":[35,197],"time,":[36],"yet":[37],"their":[38],"performance":[39],"can":[40],"seriously":[41],"deteriorate":[42],"when":[43],"the":[44,96,105,118,130,149,166],"discrepancy":[45],"distributions":[47],"large.":[49],"In":[50],"contrast,":[51],"score-based":[52],"yield":[56],"more":[57],"accurate":[58],"estimates":[59],"in":[60,168],"such":[61],"settings,":[62],"they":[64],"typically":[65],"require":[66],"considerable":[67],"repeated":[68],"function":[69,112,141],"evaluations":[70],"numerical":[72,133],"integration.":[73],"We":[74,143],"propose":[75],"One-step":[76],"Score-based":[77],"Ratio":[79],"Estimation":[80],"(OS-DRE),":[81],"partly":[83],"analytic":[84,109,150],"solver-free":[86],"framework":[87,167],"designed":[88],"to":[89],"combine":[90],"these":[91],"complementary":[92],"advantages.":[93],"OS-DRE":[94,188],"decomposes":[95],"time":[97],"score":[98],"into":[99,123],"spatial":[100],"temporal":[102,121,163],"components,":[103],"representing":[104],"latter":[106],"with":[107,138],"an":[108],"radial":[110],"basis":[111],"(RBF)":[113],"frame.":[114],"This":[115],"formulation":[116],"converts":[117],"otherwise":[119],"intractable":[120],"integral":[122],"closed-form":[125],"weighted":[126],"sum,":[127],"thereby":[128],"removing":[129],"need":[131],"solvers":[134],"enabling":[136],"only":[139],"one":[140],"evaluation.":[142],"further":[144],"analyze":[145],"approximation":[146,154,170],"conditions":[147],"frame,":[151],"establish":[153],"error":[155],"bounds":[156],"both":[158],"finitely":[159],"infinitely":[161],"smooth":[162],"kernels,":[164],"grounding":[165],"theory.":[171],"Experiments":[172],"across":[173],"density":[174],"estimation,":[175,181],"continual":[176],"Kullback-Leibler":[177],"mutual":[179],"information":[180],"near":[183],"out-of-distribution":[184],"detection":[185],"demonstrate":[186],"that":[187],"offers":[189],"favorable":[191],"balance":[192]},"counts_by_year":[],"updated_date":"2026-04-15T06:04:33.058270","created_date":"2026-04-15T00:00:00"}
