{"id":"https://openalex.org/W6906096957","doi":"https://doi.org/10.15496/publikation-72542","title":"Simulation-Based Inference for Neuroscience and Beyond","display_name":"Simulation-Based Inference for Neuroscience and Beyond","publication_year":2022,"publication_date":"2022-08-24","ids":{"openalex":"https://openalex.org/W6906096957","doi":"https://doi.org/10.15496/publikation-72542"},"language":"en","primary_location":{"id":"doi:10.15496/publikation-72542","is_oa":true,"landing_page_url":"https://doi.org/10.15496/publikation-72542","pdf_url":null,"source":{"id":"https://openalex.org/S7407053000","display_name":"Universit\u00e4tsbibliothek T\u00fcbingen","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"other","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.15496/publikation-72542","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"L\u00fcckmann, Jan-Matthis","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"L\u00fcckmann, Jan-Matthis","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":1,"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":true,"primary_topic":null,"topics":[],"keywords":[{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.7523000240325928},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.6121000051498413},{"id":"https://openalex.org/keywords/statistical-inference","display_name":"Statistical inference","score":0.5655999779701233},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4982999861240387},{"id":"https://openalex.org/keywords/statistical-model","display_name":"Statistical model","score":0.4767000079154968},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.45719999074935913},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.3716000020503998},{"id":"https://openalex.org/keywords/statistical-theory","display_name":"Statistical theory","score":0.3560999929904938}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7523000240325928},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7163000106811523},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6481999754905701},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6399000287055969},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.6121000051498413},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.5655999779701233},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4982999861240387},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.4767000079154968},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.45719999074935913},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.3716000020503998},{"id":"https://openalex.org/C48057537","wikidata":"https://www.wikidata.org/wiki/Q3551145","display_name":"Statistical theory","level":2,"score":0.3560999929904938},{"id":"https://openalex.org/C15286952","wikidata":"https://www.wikidata.org/wiki/Q8037925","display_name":"Computational neuroscience","level":2,"score":0.3416999876499176},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.3215999901294708},{"id":"https://openalex.org/C95167961","wikidata":"https://www.wikidata.org/wiki/Q4483495","display_name":"Fiducial inference","level":5,"score":0.2962000072002411},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.29510000348091125},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.2736999988555908},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.2605000138282776},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2549999952316284},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.2538999915122986},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.25209999084472656}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.15496/publikation-72542","is_oa":true,"landing_page_url":"https://doi.org/10.15496/publikation-72542","pdf_url":null,"source":{"id":"https://openalex.org/S7407053000","display_name":"Universit\u00e4tsbibliothek T\u00fcbingen","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.15496/publikation-72542","is_oa":true,"landing_page_url":"https://doi.org/10.15496/publikation-72542","pdf_url":null,"source":{"id":"https://openalex.org/S7407053000","display_name":"Universit\u00e4tsbibliothek T\u00fcbingen","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"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":{"Science":[0],"makes":[1],"extensive":[2],"use":[3,283],"of":[4,74,146,185,202,226,235,242,250,276,284],"simulations":[5,57],"to":[6,35,84,86,101,114,134,219,239,288,296,328,333,335],"model":[7],"the":[8,22,87,117,126,157,161,168,183,211,224,231,248,255,277,282,308,317,322,326],"world.":[9],"Statistical":[10],"inference":[11,31,47,55,96],"identifies":[12],"which":[13,67,99,181,229,293],"models":[14,38,145,221,241],"are":[15,44,150,230,299],"consistent":[16],"with":[17,64,97],"observed":[18],"phenomena,":[19],"thus":[20,61],"bridging":[21],"gap":[23],"between":[24,144,257],"theory":[25],"and":[26,59,116,130,140,253,259,332,338],"reality.":[27],"However,":[28],"conventional":[29],"statistical":[30,54,95,258],"is":[32],"often":[33],"inapplicable":[34],"detailed":[36],"simulation":[37],"because":[39],"their":[40],"associated":[41],"likelihood":[42],"functions":[43],"intractable.":[45],"Simulation-based":[46],"(SBI)":[48],"addresses":[49],"this":[50,106,108,165],"problem:":[51],"It":[52],"allows":[53,100,294],"from":[56,90],"alone":[58],"can":[60],"be":[62],"used":[63],"implicit":[65],"models,":[66,238],"lack":[68],"evaluable":[69],"likelihoods.":[70],"This":[71,279],"thesis":[72,109],"consists":[73],"four":[75],"publications":[76],"that":[77,149,270,298],"draw":[78],"on":[79],"advances":[80],"in":[81,138,164,197,222,306],"machine":[82],"learning":[83,201,273,286],"contribute":[85,334],"transition":[88],"away":[89],"heuristic":[91,251],"approaches":[92],"towards":[93],"principled":[94],"SBI,":[98,307],"identify":[102],"data-consistent":[103],"models.":[104,261],"To":[105],"end,":[107],"proposes":[110,265],"new":[111,291],"algorithms,":[112],"applications":[113],"neuroscience,":[115,198],"first":[118,169,323],"unified":[119,312],"benchmark":[120,313,324],"for":[121,128,160,176,205,310,325],"SBI.":[122],"Overall,":[123],"it":[124],"shows":[125],"potential":[127],"fast":[129],"flexible":[131],"likelihood-free":[132],"algorithms":[133],"facilitate":[135],"scientific":[136],"discovery":[137],"neuroscience":[139],"beyond.":[141],"The":[142,262],"trade-off":[143],"neural":[147,178,243],"dynamics":[148],"statistically":[151],"amenable":[152],"or":[153],"mechanistically":[154],"plausible":[155],"was":[156],"starting":[158],"point":[159],"work":[162],"presented":[163],"thesis.":[166],"In":[167,210,316],"publication,":[170,213,319],"we":[171,214,320],"introduce":[172],"an":[173,186,274],"SBI":[174,268],"algorithm":[175,269],"sequential":[177],"posterior":[179],"estimation,":[180],"overcomes":[182,247],"drawbacks":[184],"earlier":[187],"method.":[188],"We":[189],"provide":[190],"several":[191],"extensions":[192],"motivated":[193],"by":[194,272],"challenging":[195],"problems":[196,297],"including":[199],"end-to-end":[200],"summary":[203],"statistics":[204],"high-dimensional":[206],"time":[207],"series":[208],"data.":[209],"second":[212],"demonstrate":[215],"its":[216],"broad":[217],"applicability":[218],"mechanistic":[220,260],"neuroscience\u2014from":[223],"scale":[225],"ion":[227],"channels,":[228],"basic":[232],"building":[233],"blocks":[234],"biophysical":[236],"neuron":[237],"network":[240],"dynamics.":[244],"Our":[245],"approach":[246,280],"limitations":[249],"alternatives":[252],"narrows":[254],"divide":[256],"third":[263],"publication":[264],"a":[266,311],"novel":[267],"proceeds":[271],"emulator":[275],"simulator.":[278],"enables":[281],"active":[285],"schemes":[287],"adaptively":[289],"acquire":[290],"simulations,":[292],"scaling":[295],"computationally":[300],"highly":[301],"expensive.":[302],"With":[303],"rapid":[304],"progress":[305,331],"need":[309],"became":[314],"apparent:":[315],"fourth":[318],"propose":[321],"field":[327],"transparently":[329],"evaluate":[330],"more":[336],"efficient":[337],"reproducible":[339],"science.":[340]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}