Get quick answers to your questions about the article from our AI researcher chatbot
{'id': 'https://openalex.org/W1541011473', 'doi': 'https://doi.org/10.1109/tsp.2016.2558166', 'title': 'The Chopthin Algorithm for Resampling', 'display_name': 'The Chopthin Algorithm for Resampling', 'publication_year': 2016, 'publication_date': '2016-04-25', 'ids': {'openalex': 'https://openalex.org/W1541011473', 'doi': 'https://doi.org/10.1109/tsp.2016.2558166', 'mag': '1541011473'}, 'language': 'en', 'primary_location': {'is_oa': False, 'landing_page_url': 'https://doi.org/10.1109/tsp.2016.2558166', 'pdf_url': None, 'source': {'id': 'https://openalex.org/S168680287', 'display_name': 'IEEE Transactions on Signal Processing', 'issn_l': '1053-587X', 'issn': ['1053-587X', '1941-0476'], 'is_oa': False, 'is_in_doaj': False, 'is_core': True, 'host_organization': 'https://openalex.org/P4310319808', 'host_organization_name': 'Institute of Electrical and Electronics Engineers', 'host_organization_lineage': ['https://openalex.org/P4310319808'], 'host_organization_lineage_names': ['Institute of Electrical and Electronics Engineers'], 'type': 'journal'}, 'license': None, 'license_id': None, 'version': None, 'is_accepted': False, 'is_published': False}, 'type': 'article', 'type_crossref': 'journal-article', 'indexed_in': ['arxiv', 'crossref', 'datacite'], 'open_access': {'is_oa': True, 'oa_status': 'green', 'oa_url': 'http://arxiv.org/pdf/1502.07532', 'any_repository_has_fulltext': True}, 'authorships': [{'author_position': 'first', 'author': {'id': 'https://openalex.org/A5043216872', 'display_name': 'Axel Gandy', 'orcid': 'https://orcid.org/0000-0002-6777-0451'}, 'institutions': [{'id': 'https://openalex.org/I47508984', 'display_name': 'Imperial College London', 'ror': 'https://ror.org/041kmwe10', 'country_code': 'GB', 'type': 'education', 'lineage': ['https://openalex.org/I47508984']}], 'countries': ['GB'], 'is_corresponding': False, 'raw_author_name': 'Axel Gandy', 'raw_affiliation_strings': ['Imperial College London, London, U.K#TAB#'], 'affiliations': [{'raw_affiliation_string': 'Imperial College London, London, U.K#TAB#', 'institution_ids': ['https://openalex.org/I47508984']}]}, {'author_position': 'last', 'author': {'id': 'https://openalex.org/A5054005347', 'display_name': 'F. Din-Houn Lau', 'orcid': 'https://orcid.org/0000-0003-1065-828X'}, 'institutions': [{'id': 'https://openalex.org/I47508984', 'display_name': 'Imperial College London', 'ror': 'https://ror.org/041kmwe10', 'country_code': 'GB', 'type': 'education', 'lineage': ['https://openalex.org/I47508984']}], 'countries': ['GB'], 'is_corresponding': False, 'raw_author_name': 'F. Din-Houn Lau', 'raw_affiliation_strings': ['Imperial College London, London, U.K#TAB#'], 'affiliations': [{'raw_affiliation_string': 'Imperial College London, London, U.K#TAB#', 'institution_ids': ['https://openalex.org/I47508984']}]}], 'institution_assertions': [], 'countries_distinct_count': 1, 'institutions_distinct_count': 1, 'corresponding_author_ids': [], 'corresponding_institution_ids': [], 'apc_list': None, 'apc_paid': None, 'fwci': 1.684, 'has_fulltext': True, 'fulltext_origin': 'ngrams', 'cited_by_count': 13, 'citation_normalized_percentile': {'value': 0.89961, 'is_in_top_1_percent': False, 'is_in_top_10_percent': False}, 'cited_by_percentile_year': {'min': 88, 'max': 89}, 'biblio': {'volume': '64', 'issue': '16', 'first_page': '4273', 'last_page': '4281'}, 'is_retracted': False, 'is_paratext': False, 'primary_topic': {'id': 'https://openalex.org/T10711', 'display_name': 'Target Tracking and Data Fusion in Sensor Networks', 'score': 0.9998, '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/T10711', 'display_name': 'Target Tracking and Data Fusion in Sensor Networks', 'score': 0.9998, '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/T11220', 'display_name': 'Water Systems and Optimization', 'score': 0.9979, 'subfield': {'id': 'https://openalex.org/subfields/2205', 'display_name': 'Civil and Structural Engineering'}, '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/T11698', 'display_name': 'Underwater Acoustics Research', 'score': 0.994, 'subfield': {'id': 'https://openalex.org/subfields/1910', 'display_name': 'Oceanography'}, 'field': {'id': 'https://openalex.org/fields/19', 'display_name': 'Earth and Planetary Sciences'}, 'domain': {'id': 'https://openalex.org/domains/3', 'display_name': 'Physical Sciences'}}], 'keywords': [{'id': 'https://openalex.org/keywords/resampling', 'display_name': 'Resampling', 'score': 0.947577}, {'id': 'https://openalex.org/keywords/python', 'display_name': 'Python', 'score': 0.62510026}], 'concepts': [{'id': 'https://openalex.org/C150921843', 'wikidata': 'https://www.wikidata.org/wiki/Q1170431', 'display_name': 'Resampling', 'level': 2, 'score': 0.947577}, {'id': 'https://openalex.org/C11413529', 'wikidata': 'https://www.wikidata.org/wiki/Q8366', 'display_name': 'Algorithm', 'level': 1, 'score': 0.7051172}, {'id': 'https://openalex.org/C52421305', 'wikidata': 'https://www.wikidata.org/wiki/Q1151499', 'display_name': 'Particle filter', 'level': 3, 'score': 0.6888261}, {'id': 'https://openalex.org/C519991488', 'wikidata': 'https://www.wikidata.org/wiki/Q28865', 'display_name': 'Python (programming language)', 'level': 2, 'score': 0.62510026}, {'id': 'https://openalex.org/C41008148', 'wikidata': 'https://www.wikidata.org/wiki/Q21198', 'display_name': 'Computer science', 'level': 0, 'score': 0.5968153}, {'id': 'https://openalex.org/C19499675', 'wikidata': 'https://www.wikidata.org/wiki/Q232207', 'display_name': 'Monte Carlo method', 'level': 2, 'score': 0.54983157}, {'id': 'https://openalex.org/C77553402', 'wikidata': 'https://www.wikidata.org/wiki/Q13222579', 'display_name': 'Upper and lower bounds', 'level': 2, 'score': 0.53342617}, {'id': 'https://openalex.org/C177264268', 'wikidata': 'https://www.wikidata.org/wiki/Q1514741', 'display_name': 'Set (abstract data type)', 'level': 2, 'score': 0.42178}, {'id': 'https://openalex.org/C33923547', 'wikidata': 'https://www.wikidata.org/wiki/Q395', 'display_name': 'Mathematics', 'level': 0, 'score': 0.38734946}, {'id': 'https://openalex.org/C154945302', 'wikidata': 'https://www.wikidata.org/wiki/Q11660', 'display_name': 'Artificial intelligence', 'level': 1, 'score': 0.17696309}, {'id': 'https://openalex.org/C105795698', 'wikidata': 'https://www.wikidata.org/wiki/Q12483', 'display_name': 'Statistics', 'level': 1, 'score': 0.176193}, {'id': 'https://openalex.org/C157286648', 'wikidata': 'https://www.wikidata.org/wiki/Q846780', 'display_name': 'Kalman filter', 'level': 2, 'score': 0.0}, {'id': 'https://openalex.org/C199360897', 'wikidata': 'https://www.wikidata.org/wiki/Q9143', 'display_name': 'Programming language', 'level': 1, 'score': 0.0}, {'id': 'https://openalex.org/C134306372', 'wikidata': 'https://www.wikidata.org/wiki/Q7754', 'display_name': 'Mathematical analysis', 'level': 1, 'score': 0.0}, {'id': 'https://openalex.org/C111919701', 'wikidata': 'https://www.wikidata.org/wiki/Q9135', 'display_name': 'Operating system', 'level': 1, 'score': 0.0}], 'mesh': [], 'locations_count': 5, 'locations': [{'is_oa': False, 'landing_page_url': 'https://doi.org/10.1109/tsp.2016.2558166', 'pdf_url': None, 'source': {'id': 'https://openalex.org/S168680287', 'display_name': 'IEEE Transactions on Signal Processing', 'issn_l': '1053-587X', 'issn': ['1053-587X', '1941-0476'], 'is_oa': False, 'is_in_doaj': False, 'is_core': True, 'host_organization': 'https://openalex.org/P4310319808', 'host_organization_name': 'Institute of Electrical and Electronics Engineers', 'host_organization_lineage': ['https://openalex.org/P4310319808'], 'host_organization_lineage_names': ['Institute of Electrical and Electronics Engineers'], 'type': 'journal'}, 'license': None, 'license_id': None, 'version': None, 'is_accepted': False, 'is_published': False}, {'is_oa': True, 'landing_page_url': 'http://arxiv.org/abs/1502.07532', 'pdf_url': 'http://arxiv.org/pdf/1502.07532', 'source': {'id': 'https://openalex.org/S4306400194', 'display_name': 'arXiv (Cornell University)', 'issn_l': None, 'issn': None, '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': ['Cornell University'], 'type': 'repository'}, 'license': None, 'license_id': None, 'version': 'submittedVersion', 'is_accepted': False, 'is_published': False}, {'is_oa': True, 'landing_page_url': 'https://arxiv.org/abs/1502.07532', 'pdf_url': 'https://arxiv.org/pdf/1502.07532', 'source': {'id': 'https://openalex.org/S4306400194', 'display_name': 'arXiv (Cornell University)', 'issn_l': None, 'issn': None, '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': ['Cornell University'], 'type': 'repository'}, 'license': None, 'license_id': None, 'version': 'submittedVersion', 'is_accepted': False, 'is_published': False}, {'is_oa': True, 'landing_page_url': 'http://hdl.handle.net/10044/1/30887', 'pdf_url': 'http://spiral.imperial.ac.uk/bitstream/10044/1/30887/4/chopthin.pdf', 'source': {'id': 'https://openalex.org/S4306401396', 'display_name': 'Spiral (Imperial College London)', 'issn_l': None, 'issn': None, 'is_oa': True, 'is_in_doaj': False, 'is_core': False, 'host_organization': 'https://openalex.org/I47508984', 'host_organization_name': 'Imperial College London', 'host_organization_lineage': ['https://openalex.org/I47508984'], 'host_organization_lineage_names': ['Imperial College London'], 'type': 'repository'}, 'license': None, 'license_id': None, 'version': 'submittedVersion', 'is_accepted': False, 'is_published': False}, {'is_oa': False, 'landing_page_url': 'https://api.datacite.org/dois/10.48550/arxiv.1502.07532', 'pdf_url': None, 'source': {'id': 'https://openalex.org/S4393179698', 'display_name': 'DataCite API', 'issn_l': None, 'issn': None, 'is_oa': True, 'is_in_doaj': False, 'is_core': False, 'host_organization': 'https://openalex.org/I4210145204', 'host_organization_name': 'DataCite', 'host_organization_lineage': ['https://openalex.org/I4210145204'], 'host_organization_lineage_names': ['DataCite'], 'type': 'metadata'}, 'license': None, 'license_id': None, 'version': None}], 'best_oa_location': {'is_oa': True, 'landing_page_url': 'http://arxiv.org/abs/1502.07532', 'pdf_url': 'http://arxiv.org/pdf/1502.07532', 'source': {'id': 'https://openalex.org/S4306400194', 'display_name': 'arXiv (Cornell University)', 'issn_l': None, 'issn': None, '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': ['Cornell University'], 'type': 'repository'}, 'license': None, 'license_id': None, 'version': 'submittedVersion', 'is_accepted': False, 'is_published': False}, 'sustainable_development_goals': [], 'grants': [], 'datasets': [], 'versions': ['https://openalex.org/W1541011473'], 'referenced_works_count': 18, 'referenced_works': ['https://openalex.org/W1483307070', 'https://openalex.org/W1501586228', 'https://openalex.org/W1573874356', 'https://openalex.org/W2003456014', 'https://openalex.org/W2047094503', 'https://openalex.org/W2057665853', 'https://openalex.org/W2064119066', 'https://openalex.org/W2064480843', 'https://openalex.org/W2077611006', 'https://openalex.org/W2082542916', 'https://openalex.org/W2089805565', 'https://openalex.org/W2105934661', 'https://openalex.org/W2123726866', 'https://openalex.org/W2130363011', 'https://openalex.org/W2141585124', 'https://openalex.org/W3103996751', 'https://openalex.org/W4230410880', 'https://openalex.org/W4233487859'], 'related_works': ['https://openalex.org/W3144709167', 'https://openalex.org/W2927378857', 'https://openalex.org/W2801696468', 'https://openalex.org/W2406829934', 'https://openalex.org/W2185006999', 'https://openalex.org/W2162253570', 'https://openalex.org/W2138381686', 'https://openalex.org/W2010934810', 'https://openalex.org/W1824810860', 'https://openalex.org/W1583020711'], 'abstract_inverted_index': {'Resampling': [0], 'is': [1, 113], 'a': [2, 36, 88], 'standard': [3, 28, 64], 'step': [4], 'in': [5, 115], 'particle': [6], 'filters': [7], 'and': [8, 75, 127], 'more': [9], 'generally': [10], 'sequential': [11], 'Monte': [12], 'Carlo': [13], 'methods.': [14, 66], 'We': [15, 106], 'present': [16], 'an': [17, 46], 'algorithm,': [18], 'called': [19], 'chopthin,': [20], 'for': [21, 121], 'resampling': [22, 29, 65], 'weighted': [23, 40], 'particles.': [24, 119], 'In': [25], 'contrast': [26], 'to': [27], 'methods': [30], 'the': [31, 50, 53, 59, 92, 109, 116], 'algorithm': [32, 61, 97], 'does': [33], 'not': [34], 'produce': [35], 'set': [37], 'of': [38, 118], 'equally': [39], 'particles;': [41], 'instead': [42], 'it': [43, 103], 'merely': [44], 'enforces': [45], 'upper': [47], 'bound': [48, 90], 'on': [49, 91], 'ratio': [51], 'between': [52], 'weights.': [54], 'Simulation': [55], 'studies': [56], 'show': [57, 107], 'that': [58, 108], 'chopthin': [60], 'consistently': [62], 'outperforms': [63], 'The': [67, 96], 'algorithms': [68], 'chops': [69], 'up': [70], 'particles': [71, 78], 'with': [72, 79], 'large': [73], 'weight': [74], 'thins': [76], 'out': [77], 'low': [80], 'weight,': [81], 'hence': [82], 'its': [83], 'name.': [84], 'It': [85], 'implicitly': [86], 'guarantees': [87], 'lower': [89], 'effective': [93], 'sample': [94], 'size.': [95], 'can': [98], 'be': [99], 'implemented': [100], 'efficiently,': [101], 'making': [102], 'practically': [104], 'useful.': [105], 'expected': [110], 'computational': [111], 'effort': [112], 'linear': [114], 'number': [117], 'Implementations': [120], 'C++,': [122], 'R': [123], '(on': [124], 'CRAN),': [125], 'Python': [126], 'Matlab': [128], 'are': [129], 'available.': [130]}, 'cited_by_api_url': 'https://api.openalex.org/works?filter=cites:W1541011473', 'counts_by_year': [{'year': 2023, 'cited_by_count': 1}, {'year': 2022, 'cited_by_count': 1}, {'year': 2021, 'cited_by_count': 1}, {'year': 2020, 'cited_by_count': 1}, {'year': 2018, 'cited_by_count': 4}, {'year': 2017, 'cited_by_count': 2}, {'year': 2016, 'cited_by_count': 1}, {'year': 2015, 'cited_by_count': 2}], 'updated_date': '2025-01-06T21:02:21.616648', 'created_date': '2016-06-24'}