{"id":"https://openalex.org/W4414909457","doi":"https://doi.org/10.1109/icbc64466.2025.11185091","title":"Channel Balance Interpolation in the Lightning Network via Machine Learning","display_name":"Channel Balance Interpolation in the Lightning Network via Machine Learning","publication_year":2025,"publication_date":"2025-06-02","ids":{"openalex":"https://openalex.org/W4414909457","doi":"https://doi.org/10.1109/icbc64466.2025.11185091"},"language":"en","primary_location":{"id":"doi:10.1109/icbc64466.2025.11185091","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icbc64466.2025.11185091","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Blockchain and Cryptocurrency (ICBC)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114439127","display_name":"Vincent Davis","orcid":null},"institutions":[{"id":"https://openalex.org/I4210133331","display_name":"AM Technologies (Poland)","ror":"https://ror.org/03jpvv707","country_code":"PL","type":"company","lineage":["https://openalex.org/I4210133331"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Vincent Davis","raw_affiliation_strings":["Amboss Technologies,Nashville,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Amboss Technologies,Nashville,USA","institution_ids":["https://openalex.org/I4210133331"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005123405","display_name":"Vikash Singh","orcid":"https://orcid.org/0000-0002-6904-1199"},"institutions":[{"id":"https://openalex.org/I4210101542","display_name":"Benchmark Research (United States)","ror":"https://ror.org/0185yec04","country_code":"US","type":"company","lineage":["https://openalex.org/I4210101542"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vikash Singh","raw_affiliation_strings":["Stillmark,San Francisco,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stillmark,San Francisco,USA","institution_ids":["https://openalex.org/I4210101542"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073189260","display_name":"Emanuele Rossi","orcid":"https://orcid.org/0000-0002-2104-3646"},"institutions":[{"id":"https://openalex.org/I4210100913","display_name":"Institute of Agrifood Research and Technology","ror":"https://ror.org/012zh9h13","country_code":"ES","type":"facility","lineage":["https://openalex.org/I157913058","https://openalex.org/I4210100913","https://openalex.org/I4387153040"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Emanuele Rossi","raw_affiliation_strings":["Amboss Technologies and VantAI,Barcelona,Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Amboss Technologies and VantAI,Barcelona,Spain","institution_ids":["https://openalex.org/I4210100913"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8874,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.80336345,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10787","display_name":"Lightning and Electromagnetic Phenomena","score":0.9706000089645386,"subfield":{"id":"https://openalex.org/subfields/3103","display_name":"Astronomy and Astrophysics"},"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/T10787","display_name":"Lightning and Electromagnetic Phenomena","score":0.9706000089645386,"subfield":{"id":"https://openalex.org/subfields/3103","display_name":"Astronomy and Astrophysics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.6205000281333923},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5813000202178955},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.5388000011444092},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.47130000591278076},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.4643000066280365},{"id":"https://openalex.org/keywords/lightning","display_name":"Lightning (connector)","score":0.3846000134944916},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.36739999055862427},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.3472000062465668},{"id":"https://openalex.org/keywords/protocol","display_name":"Protocol (science)","score":0.3334999978542328}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7085000276565552},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.6205000281333923},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6055999994277954},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5813000202178955},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.5388000011444092},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4932999908924103},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.47130000591278076},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.4643000066280365},{"id":"https://openalex.org/C69398868","wikidata":"https://www.wikidata.org/wiki/Q129052","display_name":"Lightning (connector)","level":3,"score":0.3846000134944916},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37049999833106995},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.36739999055862427},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.3472000062465668},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.34630000591278076},{"id":"https://openalex.org/C2780385302","wikidata":"https://www.wikidata.org/wiki/Q367158","display_name":"Protocol (science)","level":3,"score":0.3334999978542328},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3257000148296356},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.32499998807907104},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3140999972820282},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.3098999857902527},{"id":"https://openalex.org/C161218011","wikidata":"https://www.wikidata.org/wiki/Q11827794","display_name":"Multipath propagation","level":3,"score":0.3091000020503998},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.3003999888896942},{"id":"https://openalex.org/C145097563","wikidata":"https://www.wikidata.org/wiki/Q1148747","display_name":"Payment","level":2,"score":0.2994000017642975},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.2973000109195709},{"id":"https://openalex.org/C115903097","wikidata":"https://www.wikidata.org/wiki/Q7094097","display_name":"Online machine learning","level":3,"score":0.2939999997615814},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2903999984264374},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.28850001096725464},{"id":"https://openalex.org/C19247436","wikidata":"https://www.wikidata.org/wiki/Q192727","display_name":"Physical layer","level":3,"score":0.27090001106262207},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.2599000036716461},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2540999948978424},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.25270000100135803}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icbc64466.2025.11185091","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icbc64466.2025.11185091","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Blockchain and Cryptocurrency (ICBC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":3,"referenced_works":["https://openalex.org/W3091207531","https://openalex.org/W4220916980","https://openalex.org/W4405273429"],"related_works":[],"abstract_inverted_index":{"The":[0],"Bitcoin":[1],"Lightning":[2],"Network":[3],"is":[4],"a":[5],"Layer":[6],"2":[7],"payment":[8,21,60],"protocol":[9],"that":[10],"addresses":[11],"Bitcoin\u2019s":[12],"scalability":[13],"by":[14,108],"facilitating":[15],"quick":[16],"and":[17,58,68,89],"cost-effective":[18],"transactions":[19],"through":[20],"channels.":[22],"This":[23,75],"research":[24],"explores":[25],"the":[26,37,45,78,91,105,123],"use":[27],"of":[28,80,94,122],"machine":[29,82],"learning":[30,83],"models":[31,84],"to":[32,111],"interpolate":[33],"channel":[34,63,69,124],"balances":[35,64],"within":[36],"network,":[38],"which":[39],"can":[40],"be":[41],"used":[42],"for":[43],"optimizing":[44],"network\u2019s":[46],"pathfinding":[47],"algorithms.":[48],"While":[49],"there":[50],"has":[51],"been":[52],"much":[53],"exploration":[54],"in":[55,101],"balance":[56],"probing":[57],"multipath":[59],"protocols,":[61],"predicting":[62],"using":[65],"solely":[66],"node":[67],"features":[70],"remains":[71],"an":[72,112],"uncharted":[73],"area.":[74],"paper":[76],"evaluates":[77],"performance":[79],"several":[81],"against":[85],"two":[86],"heuristic":[87],"baselines":[88],"investigates":[90],"predictive":[92],"capabilities":[93],"various":[95],"features.":[96],"Our":[97],"model":[98],"performs":[99],"favorably":[100],"experimental":[102],"evaluation,":[103],"reducing":[104],"relative":[106],"error":[107],"27%":[109],"compared":[110],"equal":[113],"split":[114],"baseline":[115],"where":[116],"both":[117],"edges":[118],"are":[119],"assigned":[120],"half":[121],"capacity.":[125]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}