{"id":"https://openalex.org/W7162106202","doi":"https://doi.org/10.2312/egp.20261003","title":"Neural Approximation of Generalized Voronoi Diagrams","display_name":"Neural Approximation of Generalized Voronoi Diagrams","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7162106202","doi":"https://doi.org/10.2312/egp.20261003"},"language":null,"primary_location":{"id":"doi:10.2312/egp.20261003","is_oa":true,"landing_page_url":"https://doi.org/10.2312/egp.20261003","pdf_url":null,"source":{"id":"https://openalex.org/S7407052899","display_name":"Eurographics","issn_l":null,"issn":null,"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":"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-journal"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.2312/egp.20261003","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5125909296","display_name":"Panagiotis Rigas","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rigas, Panagiotis","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135421882","display_name":"George Ioannakis","orcid":"https://orcid.org/0000-0001-6230-7030"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ioannakis, George","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136766247","display_name":"Ioannis Emiris","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Emiris, Ioannis","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.64852124,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.5741999745368958,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.5741999745368958,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10996","display_name":"Computational Geometry and Mesh Generation","score":0.1906999945640564,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/T12536","display_name":"Topological and Geometric Data Analysis","score":0.08950000256299973,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/voronoi-diagram","display_name":"Voronoi diagram","score":0.604200005531311},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42289999127388},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.3075000047683716},{"id":"https://openalex.org/keywords/diagram","display_name":"Diagram","score":0.2806999981403351},{"id":"https://openalex.org/keywords/approximation-algorithm","display_name":"Approximation algorithm","score":0.2750000059604645},{"id":"https://openalex.org/keywords/centroidal-voronoi-tessellation","display_name":"Centroidal Voronoi tessellation","score":0.26759999990463257}],"concepts":[{"id":"https://openalex.org/C24881265","wikidata":"https://www.wikidata.org/wiki/Q757267","display_name":"Voronoi diagram","level":2,"score":0.604200005531311},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4544999897480011},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42289999127388},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3788999915122986},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3075000047683716},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.30730000138282776},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3057999908924103},{"id":"https://openalex.org/C186399060","wikidata":"https://www.wikidata.org/wiki/Q959962","display_name":"Diagram","level":2,"score":0.2806999981403351},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.27900001406669617},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.2750000059604645},{"id":"https://openalex.org/C205672865","wikidata":"https://www.wikidata.org/wiki/Q5062961","display_name":"Centroidal Voronoi tessellation","level":3,"score":0.26759999990463257},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.26750001311302185},{"id":"https://openalex.org/C129844170","wikidata":"https://www.wikidata.org/wiki/Q41299","display_name":"Quadratic equation","level":2,"score":0.2632000148296356},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.2583000063896179}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.2312/egp.20261003","is_oa":true,"landing_page_url":"https://doi.org/10.2312/egp.20261003","pdf_url":null,"source":{"id":"https://openalex.org/S7407052899","display_name":"Eurographics","issn_l":null,"issn":null,"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":"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-journal"}],"best_oa_location":{"id":"doi:10.2312/egp.20261003","is_oa":true,"landing_page_url":"https://doi.org/10.2312/egp.20261003","pdf_url":null,"source":{"id":"https://openalex.org/S7407052899","display_name":"Eurographics","issn_l":null,"issn":null,"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":"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-journal"},"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":{"We":[0],"introduce":[1],"VoroFields,":[2],"a":[3,33],"hierarchical":[4,64],"neural-field":[5],"framework":[6],"for":[7],"approximating":[8],"generalized":[9],"Voronoi":[10,45],"diagrams":[11],"of":[12,26,51,86],"finite":[13],"geometric":[14],"site":[15,79],"sets":[16],"in":[17],"low-dimensional":[18],"domains":[19],"under":[20],"arbitrary":[21],"evaluable":[22],"point-to-site":[23],"distances.":[24],"Instead":[25],"constructing":[27],"the":[28,41,52,67],"diagram":[29],"combinatorially,":[30],"VoroFields":[31],"learns":[32],"continuous,":[34],"differentiable":[35],"surrogate":[36],"whose":[37],"maximizer":[38,49],"structure":[39],"induces":[40],"partition":[42],"implicitly.":[43],"The":[44],"cells":[46,87],"correspond":[47],"to":[48],"regions":[50],"field,":[53],"with":[54],"boundaries":[55],"defined":[56],"by":[57,70],"equal":[58],"responses":[59],"between":[60],"competing":[61],"sites.":[62],"A":[63],"decomposition":[65],"reduces":[66],"combinatorial":[68],"complexity":[69],"refining":[71],"only":[72],"near":[73],"envelope":[74],"transition":[75],"strata.":[76],"Experiments":[77],"across":[78],"families":[80],"and":[81,88],"metrics":[82],"demonstrate":[83],"accurate":[84],"recovery":[85],"boundary":[89],"geometry":[90],"without":[91],"shape-specific":[92],"constructions.":[93]},"counts_by_year":[],"updated_date":"2026-05-27T06:14:07.914337","created_date":"2026-05-23T00:00:00"}