{"id":"https://openalex.org/W7133344936","doi":"https://doi.org/10.48550/arxiv.2603.00530","title":"Bridge Matching Sampler: Scalable Sampling via Generalized Fixed-Point Diffusion Matching","display_name":"Bridge Matching Sampler: Scalable Sampling via Generalized Fixed-Point Diffusion Matching","publication_year":2026,"publication_date":"2026-02-28","ids":{"openalex":"https://openalex.org/W7133344936","doi":"https://doi.org/10.48550/arxiv.2603.00530"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.00530","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.00530","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.2603.00530","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5012897974","display_name":"Denis Blessing","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Blessing, Denis","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049655393","display_name":"Lorenz Richter","orcid":"https://orcid.org/0000-0001-5028-5639"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Richter, Lorenz","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127997941","display_name":"Julius Berner","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Berner, Julius","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127988553","display_name":"Egor Malitskiy","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Malitskiy, Egor","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5127920518","display_name":"Gerhard Neumann","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Neumann, Gerhard","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5012897974"],"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/T11206","display_name":"Model Reduction and Neural Networks","score":0.20720000565052032,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.20720000565052032,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.13950000703334808,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.12479999661445618,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.6209999918937683},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6141999959945679},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.6085000038146973},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.48190000653266907},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.4715999960899353},{"id":"https://openalex.org/keywords/diffusion","display_name":"Diffusion","score":0.45239999890327454},{"id":"https://openalex.org/keywords/importance-sampling","display_name":"Importance sampling","score":0.4320000112056732},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.41589999198913574},{"id":"https://openalex.org/keywords/mode","display_name":"Mode (computer interface)","score":0.39640000462532043}],"concepts":[{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.6209999918937683},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6141999959945679},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6085000038146973},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6061999797821045},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5666999816894531},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.48339998722076416},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.48190000653266907},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.4715999960899353},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.45239999890327454},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.4320000112056732},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.41589999198913574},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.39640000462532043},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.3905999958515167},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.3799000084400177},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3314000070095062},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3199999928474426},{"id":"https://openalex.org/C8272713","wikidata":"https://www.wikidata.org/wiki/Q176737","display_name":"Stochastic process","level":2,"score":0.3167000114917755},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3052999973297119},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.29280000925064087},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.2784000039100647},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.2775999903678894},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2770000100135803},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.2743000090122223},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.2709999978542328},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.26429998874664307},{"id":"https://openalex.org/C123853557","wikidata":"https://www.wikidata.org/wiki/Q7098946","display_name":"Optimal matching","level":3,"score":0.2540000081062317},{"id":"https://openalex.org/C20326153","wikidata":"https://www.wikidata.org/wiki/Q7049638","display_name":"Nonuniform sampling","level":3,"score":0.2524999976158142},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.25}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.00530","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.00530","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.2603.00530","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.00530","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":{"Sampling":[0],"from":[1],"unnormalized":[2],"densities":[3,133],"using":[4],"diffusion":[5],"models":[6],"has":[7],"emerged":[8],"as":[9,31,45],"a":[10,57,73,84,93,101],"powerful":[11],"paradigm.":[12],"However,":[13],"while":[14,123],"recent":[15],"approaches":[16],"that":[17,60,99,115],"use":[18],"least-squares":[19],"`matching'":[20],"objectives":[21],"have":[22],"improved":[23],"scalability,":[24],"they":[25],"often":[26],"necessitate":[27],"significant":[28],"trade-offs,":[29],"such":[30],"restricting":[32],"prior":[33,79],"distributions":[34,82],"or":[35],"relying":[36],"on":[37,130],"unstable":[38],"optimization":[39],"schemes.":[40],"By":[41],"generalizing":[42],"these":[43,62],"methods":[44],"special":[46],"forms":[47],"of":[48,96],"fixed-point":[49],"iterations":[50],"rooted":[51],"in":[52],"Nelson's":[53],"relation,":[54],"we":[55,91,113],"develop":[56],"new":[58],"method":[59,117],"addresses":[61],"limitations,":[63],"called":[64],"Bridge":[65],"Matching":[66],"Sampler":[67],"(BMS).":[68],"Our":[69],"approach":[70],"enables":[71,118],"learning":[72],"stochastic":[74],"transport":[75],"map":[76],"between":[77],"arbitrary":[78],"and":[80,87,108,134],"target":[81],"with":[83],"single,":[85],"scalable,":[86],"stable":[88],"objective.":[89],"Furthermore,":[90],"introduce":[92],"damped":[94],"variant":[95],"this":[97],"iteration":[98],"incorporates":[100],"regularization":[102],"term":[103],"to":[104],"mitigate":[105],"mode":[106,125],"collapse":[107],"further":[109],"stabilize":[110],"training.":[111],"Empirically,":[112],"demonstrate":[114],"our":[116],"sampling":[119],"at":[120],"unprecedented":[121],"scales":[122],"preserving":[124],"diversity,":[126],"achieving":[127],"state-of-the-art":[128],"results":[129],"complex":[131],"synthetic":[132],"high-dimensional":[135],"molecular":[136],"benchmarks.":[137]},"counts_by_year":[],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2026-03-04T00:00:00"}
