{"id":"https://openalex.org/W7125714474","doi":"https://doi.org/10.48550/arxiv.2601.16936","title":"Is BatchEnsemble a Single Model? On Calibration and Diversity of Efficient Ensembles","display_name":"Is BatchEnsemble a Single Model? On Calibration and Diversity of Efficient Ensembles","publication_year":2026,"publication_date":"2026-01-23","ids":{"openalex":"https://openalex.org/W7125714474","doi":"https://doi.org/10.48550/arxiv.2601.16936"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2601.16936","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.16936","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.2601.16936","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5123851183","display_name":"Anton Zamyatin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zamyatin, Anton","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123879228","display_name":"Patrick Indri","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Indri, Patrick","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086702765","display_name":"Sagar Malhotra","orcid":"https://orcid.org/0000-0002-5509-0168"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Malhotra, Sagar","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5025793777","display_name":"Thomas G\u00e4rtner","orcid":"https://orcid.org/0000-0001-5985-9213"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"G\u00e4rtner, Thomas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.47360000014305115,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.47360000014305115,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.14499999582767487,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.08470000326633453,"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/calibration","display_name":"Calibration","score":0.7620999813079834},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.5789999961853027},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.557200014591217},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.5199000239372253},{"id":"https://openalex.org/keywords/base","display_name":"Base (topology)","score":0.5030999779701233},{"id":"https://openalex.org/keywords/uncertainty-quantification","display_name":"Uncertainty quantification","score":0.296099990606308}],"concepts":[{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.7620999813079834},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.5789999961853027},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.557200014591217},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.538100004196167},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.5199000239372253},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5051000118255615},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.5030999779701233},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43059998750686646},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3668999969959259},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3528999984264374},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3395000100135803},{"id":"https://openalex.org/C32230216","wikidata":"https://www.wikidata.org/wiki/Q7882499","display_name":"Uncertainty quantification","level":2,"score":0.296099990606308},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.28119999170303345},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.275299996137619},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.2720000147819519},{"id":"https://openalex.org/C2781316041","wikidata":"https://www.wikidata.org/wiki/Q1230584","display_name":"Diversity (politics)","level":2,"score":0.2662999927997589},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.26440000534057617},{"id":"https://openalex.org/C94361409","wikidata":"https://www.wikidata.org/wiki/Q7882500","display_name":"Uncertainty reduction theory","level":2,"score":0.25619998574256897}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2601.16936","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.16936","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.2601.16936","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.16936","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":{"In":[0],"resource-constrained":[1],"and":[2,34,68,85],"low-latency":[3],"settings,":[4],"uncertainty":[5,16],"estimates":[6],"must":[7],"be":[8],"efficiently":[9],"obtained.":[10],"Deep":[11,54],"Ensembles":[12,55],"provide":[13],"robust":[14],"epistemic":[15],"(EU)":[17],"but":[18,56],"require":[19],"training":[20],"multiple":[21],"full-size":[22],"models.":[23],"BatchEnsemble":[24,50,97],"aims":[25],"to":[26,42,91],"deliver":[27],"ensemble-like":[28],"EU":[29],"at":[30],"far":[31],"lower":[32],"parameter":[33,86],"memory":[35],"cost":[36],"by":[37],"applying":[38],"learned":[39],"rank-1":[40],"perturbations":[41],"a":[43,59,101,105],"shared":[44],"base":[45],"network.":[46],"We":[47],"show":[48],"that":[49],"not":[51],"only":[52],"underperforms":[53],"closely":[57],"tracks":[58],"single":[60,102],"model":[61,103],"baseline":[62],"in":[63,83],"terms":[64],"of":[65],"accuracy,":[66],"calibration":[67],"out-of-distribution":[69],"(OOD)":[70],"detection":[71],"on":[72,77],"CIFAR10/10C/SVHN.":[73],"A":[74],"controlled":[75],"study":[76],"MNIST":[78],"finds":[79],"members":[80],"are":[81],"near-identical":[82],"function":[84],"space,":[87],"indicating":[88],"limited":[89],"capacity":[90],"realize":[92],"distinct":[93],"predictive":[94],"modes.":[95],"Thus,":[96],"behaves":[98],"more":[99],"like":[100],"than":[104],"true":[106],"ensemble.":[107]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-01-27T00:00:00"}
