{"id":"https://openalex.org/W4416350698","doi":"https://doi.org/10.48550/arxiv.2511.11787","title":"Towards Mitigating Systematics in Large-Scale Surveys via Few-Shot Optimal Transport-Based Feature Alignment","display_name":"Towards Mitigating Systematics in Large-Scale Surveys via Few-Shot Optimal Transport-Based Feature Alignment","publication_year":2025,"publication_date":"2025-11-14","ids":{"openalex":"https://openalex.org/W4416350698","doi":"https://doi.org/10.48550/arxiv.2511.11787"},"language":null,"primary_location":{"id":"pmh:oai:arXiv.org:2511.11787","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2511.11787","pdf_url":"https://arxiv.org/pdf/2511.11787","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2511.11787","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5013342528","display_name":"Sultan Hassan","orcid":"https://orcid.org/0000-0002-1050-7572"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Hassan, Sultan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038445526","display_name":"Sambatra Andrianomena","orcid":"https://orcid.org/0000-0001-5957-0719"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Andrianomena, Sambatra","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5050309898","display_name":"B. D. Wandelt","orcid":"https://orcid.org/0000-0002-5854-8269"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wandelt, Benjamin D.","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5013342528"],"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/T12417","display_name":"Morphological variations and asymmetry","score":0.22100000083446503,"subfield":{"id":"https://openalex.org/subfields/2608","display_name":"Geometry and Topology"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12417","display_name":"Morphological variations and asymmetry","score":0.22100000083446503,"subfield":{"id":"https://openalex.org/subfields/2608","display_name":"Geometry and Topology"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10895","display_name":"Species Distribution and Climate Change","score":0.2004999965429306,"subfield":{"id":"https://openalex.org/subfields/2302","display_name":"Ecological Modeling"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10015","display_name":"Genomics and Phylogenetic Studies","score":0.15549999475479126,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/systematics","display_name":"Systematics","score":0.6373000144958496},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.6189000010490417},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.590499997138977},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4948999881744385},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4431999921798706},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.36730000376701355}],"concepts":[{"id":"https://openalex.org/C41806617","wikidata":"https://www.wikidata.org/wiki/Q3516404","display_name":"Systematics","level":3,"score":0.6373000144958496},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.6189000010490417},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.590499997138977},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5763000249862671},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.541700005531311},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4948999881744385},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4431999921798706},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4357999861240387},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39399999380111694},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3693999946117401},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.36730000376701355},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.325300008058548},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.2849000096321106},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.28029999136924744},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.25029999017715454}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2511.11787","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2511.11787","pdf_url":"https://arxiv.org/pdf/2511.11787","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2511.11787","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2511.11787","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2511.11787","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2511.11787","pdf_url":"https://arxiv.org/pdf/2511.11787","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"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":{"Systematics":[0],"contaminate":[1],"observables,":[2],"leading":[3],"to":[4,8,19,31,101],"distribution":[5],"shifts":[6],"relative":[7],"theoretically":[9],"simulated":[10],"signals-posing":[11],"a":[12,48,64,72],"major":[13],"challenge":[14],"for":[15],"using":[16,86],"pre-trained":[17,73],"models":[18],"label":[20],"such":[21],"observables.":[22],"Since":[23],"systematics":[24],"are":[25],"often":[26],"poorly":[27],"understood":[28],"and":[29,36,58,94,97,124],"difficult":[30],"model,":[32],"removing":[33],"them":[34],"directly":[35],"entirely":[37],"may":[38],"not":[39],"be":[40],"feasible.":[41],"To":[42],"address":[43],"this":[44],"challenge,":[45],"we":[46],"propose":[47],"novel":[49],"method":[50,81],"that":[51,110],"aligns":[52],"learned":[53],"features":[54,119],"between":[55,122],"in-distribution":[56],"(ID)":[57],"out-of-distribution":[59],"(OOD)":[60],"samples":[61,126],"by":[62],"optimizing":[63],"feature-alignment":[65],"loss":[66],"on":[67,82],"the":[68,80,83],"representations":[69],"extracted":[70],"from":[71,138],"ID":[74,123],"model.":[75],"We":[76],"first":[77],"experimentally":[78],"validate":[79],"MNIST":[84],"dataset":[85],"possible":[87],"alignment":[88],"losses,":[89],"including":[90],"mean":[91],"squared":[92],"error":[93],"optimal":[95,111],"transport,":[96],"subsequently":[98],"apply":[99],"it":[100],"large-scale":[102,139],"maps":[103],"of":[104],"neutral":[105],"hydrogen.":[106],"Our":[107,141],"results":[108],"show":[109],"transport":[112],"is":[113,127,143],"particularly":[114],"effective":[115],"at":[116,145],"aligning":[117],"OOD":[118,125],"when":[120],"parity":[121],"unknown,":[128],"even":[129],"with":[130],"limited":[131],"data-mimicking":[132],"real-world":[133],"conditions":[134],"in":[135],"extracting":[136],"information":[137],"surveys.":[140],"code":[142],"available":[144],"https://github.com/sultan-hassan/feature-alignment-for-OOD-generalization.":[146]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-11-19T00:00:00"}