Publication Information

{'id': 'https://openalex.org/W2953501176', 'doi': 'https://doi.org/10.48550/arxiv.1906.10335', 'title': 'Perceptual Generative Autoencoders', 'display_name': 'Perceptual Generative Autoencoders', 'publication_year': 2019, 'publication_date': '2019-01-01', 'ids': {'openalex': 'https://openalex.org/W2953501176', 'doi': 'https://doi.org/10.48550/arxiv.1906.10335', 'mag': '2953501176'}, 'language': 'en', 'primary_location': {'is_oa': True, 'landing_page_url': 'https://arxiv.org/abs/1906.10335', 'pdf_url': None, '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': 'other-oa', 'license_id': 'https://openalex.org/licenses/other-oa', 'version': 'submittedVersion', 'is_accepted': False, 'is_published': False}, 'type': 'preprint', 'type_crossref': 'posted-content', 'indexed_in': ['arxiv', 'datacite'], 'open_access': {'is_oa': True, 'oa_status': 'green', 'oa_url': 'https://arxiv.org/abs/1906.10335', 'any_repository_has_fulltext': True}, 'authorships': [{'author_position': 'first', 'author': {'id': 'https://openalex.org/A5100764713', 'display_name': 'Zijun Zhang', 'orcid': 'https://orcid.org/0000-0002-2717-5033'}, 'institutions': [{'id': 'https://openalex.org/I168635309', 'display_name': 'University of Calgary', 'ror': 'https://ror.org/03yjb2x39', 'country_code': 'CA', 'type': 'education', 'lineage': ['https://openalex.org/I168635309']}], 'countries': ['CA'], 'is_corresponding': False, 'raw_author_name': 'Zijun Zhang', 'raw_affiliation_strings': ['University#N#                            of Calgary'], 'affiliations': [{'raw_affiliation_string': 'University#N#                            of Calgary', 'institution_ids': ['https://openalex.org/I168635309']}]}, {'author_position': 'middle', 'author': {'id': 'https://openalex.org/A5103242473', 'display_name': 'Ruixiang Zhang', 'orcid': 'https://orcid.org/0009-0009-3728-5170'}, 'institutions': [{'id': 'https://openalex.org/I4210155582', 'display_name': 'Centre Universitaire de Mila', 'ror': 'https://ror.org/05s3cw058', 'country_code': 'DZ', 'type': 'education', 'lineage': ['https://openalex.org/I4210155582']}], 'countries': ['DZ'], 'is_corresponding': False, 'raw_author_name': 'Ruixiang Zhang', 'raw_affiliation_strings': ['MILA, UdeM'], 'affiliations': [{'raw_affiliation_string': 'MILA, UdeM', 'institution_ids': ['https://openalex.org/I4210155582']}]}, {'author_position': 'middle', 'author': {'id': 'https://openalex.org/A5066247159', 'display_name': 'Zongpeng Li', 'orcid': 'https://orcid.org/0000-0001-5351-2075'}, 'institutions': [{'id': 'https://openalex.org/I37461747', 'display_name': 'Wuhan University', 'ror': 'https://ror.org/033vjfk17', 'country_code': 'CN', 'type': 'education', 'lineage': ['https://openalex.org/I37461747']}], 'countries': ['CN'], 'is_corresponding': False, 'raw_author_name': 'Zongpeng Li', 'raw_affiliation_strings': ['Wuhan University'], 'affiliations': [{'raw_affiliation_string': 'Wuhan University', 'institution_ids': ['https://openalex.org/I37461747']}]}, {'author_position': 'middle', 'author': {'id': 'https://openalex.org/A5086198262', 'display_name': 'Yoshua Bengio', 'orcid': 'https://orcid.org/0000-0002-9322-3515'}, 'institutions': [{'id': 'https://openalex.org/I4210155582', 'display_name': 'Centre Universitaire de Mila', 'ror': 'https://ror.org/05s3cw058', 'country_code': 'DZ', 'type': 'education', 'lineage': ['https://openalex.org/I4210155582']}], 'countries': ['DZ'], 'is_corresponding': False, 'raw_author_name': 'Yoshua Bengio', 'raw_affiliation_strings': ['Mila / U. Montreal'], 'affiliations': [{'raw_affiliation_string': 'Mila / U. Montreal', 'institution_ids': ['https://openalex.org/I4210155582']}]}, {'author_position': 'last', 'author': {'id': 'https://openalex.org/A5037065865', 'display_name': 'Liam Paull', 'orcid': 'https://orcid.org/0000-0003-2492-6660'}, 'institutions': [{'id': 'https://openalex.org/I70931966', 'display_name': 'Université de Montréal', 'ror': 'https://ror.org/0161xgx34', 'country_code': 'CA', 'type': 'education', 'lineage': ['https://openalex.org/I70931966']}], 'countries': ['CA'], 'is_corresponding': False, 'raw_author_name': 'Liam Paull', 'raw_affiliation_strings': ['Universitè de Montreal'], 'affiliations': [{'raw_affiliation_string': 'Universitè de Montreal', 'institution_ids': ['https://openalex.org/I70931966']}]}], 'institution_assertions': [], 'countries_distinct_count': 3, 'institutions_distinct_count': 4, 'corresponding_author_ids': [], 'corresponding_institution_ids': [], 'apc_list': None, 'apc_paid': None, 'fwci': None, 'has_fulltext': False, 'cited_by_count': 17, 'citation_normalized_percentile': {'value': 0.999829, 'is_in_top_1_percent': True, 'is_in_top_10_percent': True}, 'cited_by_percentile_year': {'min': 90, 'max': 91}, 'biblio': {'volume': None, 'issue': None, 'first_page': None, 'last_page': None}, 'is_retracted': False, 'is_paratext': False, 'primary_topic': {'id': 'https://openalex.org/T10775', 'display_name': 'Generative Adversarial Networks and Image Synthesis', 'score': 0.9997, 'subfield': {'id': 'https://openalex.org/subfields/1707', 'display_name': 'Computer Vision and Pattern Recognition'}, '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/T10775', 'display_name': 'Generative Adversarial Networks and Image Synthesis', 'score': 0.9997, 'subfield': {'id': 'https://openalex.org/subfields/1707', 'display_name': 'Computer Vision and Pattern Recognition'}, '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/T11309', 'display_name': 'Music and Audio Processing', 'score': 0.9926, 'subfield': {'id': 'https://openalex.org/subfields/1711', 'display_name': 'Signal Processing'}, '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/T13650', 'display_name': 'Computational Physics and Python Applications', 'score': 0.9427, '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/autoencoder', 'display_name': 'Autoencoder', 'score': 0.951885}, {'id': 'https://openalex.org/keywords/generative-model', 'display_name': 'Generative model', 'score': 0.69920206}, {'id': 'https://openalex.org/keywords/intrinsic-dimension', 'display_name': 'Intrinsic dimension', 'score': 0.62027013}, {'id': 'https://openalex.org/keywords/representation', 'display_name': 'Representation', 'score': 0.4625278}], 'concepts': [{'id': 'https://openalex.org/C101738243', 'wikidata': 'https://www.wikidata.org/wiki/Q786435', 'display_name': 'Autoencoder', 'level': 3, 'score': 0.951885}, {'id': 'https://openalex.org/C60832428', 'wikidata': 'https://www.wikidata.org/wiki/Q945818', 'display_name': 'Partitioned global address space', 'level': 3, 'score': 0.76962936}, {'id': 'https://openalex.org/C167966045', 'wikidata': 'https://www.wikidata.org/wiki/Q5532625', 'display_name': 'Generative model', 'level': 3, 'score': 0.69920206}, {'id': 'https://openalex.org/C39890363', 'wikidata': 'https://www.wikidata.org/wiki/Q36108', 'display_name': 'Generative grammar', 'level': 2, 'score': 0.69164765}, {'id': 'https://openalex.org/C177769412', 'wikidata': 'https://www.wikidata.org/wiki/Q278090', 'display_name': 'Prior probability', 'level': 3, 'score': 0.6791523}, {'id': 'https://openalex.org/C33676613', 'wikidata': 'https://www.wikidata.org/wiki/Q13415176', 'display_name': 'Dimension (graph theory)', 'level': 2, 'score': 0.6468019}, {'id': 'https://openalex.org/C30732413', 'wikidata': 'https://www.wikidata.org/wiki/Q17092636', 'display_name': 'Intrinsic dimension', 'level': 3, 'score': 0.62027013}, {'id': 'https://openalex.org/C41008148', 'wikidata': 'https://www.wikidata.org/wiki/Q21198', 'display_name': 'Computer science', 'level': 0, 'score': 0.57565486}, {'id': 'https://openalex.org/C2778572836', 'wikidata': 'https://www.wikidata.org/wiki/Q380933', 'display_name': 'Space (punctuation)', 'level': 2, 'score': 0.57027614}, {'id': 'https://openalex.org/C154945302', 'wikidata': 'https://www.wikidata.org/wiki/Q11660', 'display_name': 'Artificial intelligence', 'level': 1, 'score': 0.5450322}, {'id': 'https://openalex.org/C118505674', 'wikidata': 'https://www.wikidata.org/wiki/Q42586063', 'display_name': 'Encoder', 'level': 2, 'score': 0.48044798}, {'id': 'https://openalex.org/C2780992000', 'wikidata': 'https://www.wikidata.org/wiki/Q17016113', 'display_name': 'Generator (circuit theory)', 'level': 3, 'score': 0.47260314}, {'id': 'https://openalex.org/C2776359362', 'wikidata': 'https://www.wikidata.org/wiki/Q2145286', 'display_name': 'Representation (politics)', 'level': 3, 'score': 0.4625278}, {'id': 'https://openalex.org/C153180895', 'wikidata': 'https://www.wikidata.org/wiki/Q7148389', 'display_name': 'Pattern recognition (psychology)', 'level': 2, 'score': 0.45288515}, {'id': 'https://openalex.org/C50644808', 'wikidata': 'https://www.wikidata.org/wiki/Q192776', 'display_name': 'Artificial neural network', 'level': 2, 'score': 0.43624347}, {'id': 'https://openalex.org/C119857082', 'wikidata': 'https://www.wikidata.org/wiki/Q2539', 'display_name': 'Machine learning', 'level': 1, 'score': 0.34550261}, {'id': 'https://openalex.org/C33923547', 'wikidata': 'https://www.wikidata.org/wiki/Q395', 'display_name': 'Mathematics', 'level': 0, 'score': 0.2582562}, {'id': 'https://openalex.org/C107673813', 'wikidata': 'https://www.wikidata.org/wiki/Q812534', 'display_name': 'Bayesian probability', 'level': 2, 'score': 0.09675053}, {'id': 'https://openalex.org/C111030470', 'wikidata': 'https://www.wikidata.org/wiki/Q1430460', 'display_name': 'Curse of dimensionality', 'level': 2, 'score': 0.09123373}, {'id': 'https://openalex.org/C163258240', 'wikidata': 'https://www.wikidata.org/wiki/Q25342', 'display_name': 'Power (physics)', 'level': 2, 'score': 0.06706488}, {'id': 'https://openalex.org/C121332964', 'wikidata': 'https://www.wikidata.org/wiki/Q413', 'display_name': 'Physics', 'level': 0, 'score': 0.0}, {'id': 'https://openalex.org/C62520636', 'wikidata': 'https://www.wikidata.org/wiki/Q944', 'display_name': 'Quantum mechanics', 'level': 1, 'score': 0.0}, {'id': 'https://openalex.org/C34165917', 'wikidata': 'https://www.wikidata.org/wiki/Q188267', 'display_name': 'Programming paradigm', 'level': 2, 'score': 0.0}, {'id': 'https://openalex.org/C94625758', 'wikidata': 'https://www.wikidata.org/wiki/Q7163', 'display_name': 'Politics', 'level': 2, 'score': 0.0}, {'id': 'https://openalex.org/C199539241', 'wikidata': 'https://www.wikidata.org/wiki/Q7748', 'display_name': 'Law', 'level': 1, 'score': 0.0}, {'id': 'https://openalex.org/C202444582', 'wikidata': 'https://www.wikidata.org/wiki/Q837863', 'display_name': 'Pure mathematics', 'level': 1, 'score': 0.0}, {'id': 'https://openalex.org/C17744445', 'wikidata': 'https://www.wikidata.org/wiki/Q36442', 'display_name': 'Political science', 'level': 0, '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/C111919701', 'wikidata': 'https://www.wikidata.org/wiki/Q9135', 'display_name': 'Operating system', 'level': 1, 'score': 0.0}], 'mesh': [], 'locations_count': 2, 'locations': [{'is_oa': True, 'landing_page_url': 'https://arxiv.org/abs/1906.10335', 'pdf_url': None, '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': 'other-oa', 'license_id': 'https://openalex.org/licenses/other-oa', 'version': 'submittedVersion', 'is_accepted': False, 'is_published': False}, {'is_oa': False, 'landing_page_url': 'https://api.datacite.org/dois/10.48550/arxiv.1906.10335', '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': 'https://arxiv.org/abs/1906.10335', 'pdf_url': None, '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': 'other-oa', 'license_id': 'https://openalex.org/licenses/other-oa', 'version': 'submittedVersion', 'is_accepted': False, 'is_published': False}, 'sustainable_development_goals': [], 'grants': [], 'datasets': [], 'versions': [], 'referenced_works_count': 28, 'referenced_works': ['https://openalex.org/W1834627138', 'https://openalex.org/W1836465849', 'https://openalex.org/W1959608418', 'https://openalex.org/W2025768430', 'https://openalex.org/W2099471712', 'https://openalex.org/W2134842679', 'https://openalex.org/W2528578439', 'https://openalex.org/W2739748921', 'https://openalex.org/W2787463479', 'https://openalex.org/W2893749619', 'https://openalex.org/W2907366006', 'https://openalex.org/W2927928207', 'https://openalex.org/W2962695743', 'https://openalex.org/W2962760235', 'https://openalex.org/W2962820504', 'https://openalex.org/W2962879692', 'https://openalex.org/W2963139417', 'https://openalex.org/W2963226019', 'https://openalex.org/W2963373786', 'https://openalex.org/W2963641970', 'https://openalex.org/W2963684088', 'https://openalex.org/W2963746531', 'https://openalex.org/W2963755523', 'https://openalex.org/W2963836885', 'https://openalex.org/W2963981733', 'https://openalex.org/W2964020555', 'https://openalex.org/W3038022805', 'https://openalex.org/W3118608800'], 'related_works': ['https://openalex.org/W4394785709', 'https://openalex.org/W4383368570', 'https://openalex.org/W4309969736', 'https://openalex.org/W4306309289', 'https://openalex.org/W3034474024', 'https://openalex.org/W2965095304', 'https://openalex.org/W2953501176', 'https://openalex.org/W2770818364', 'https://openalex.org/W2470043383', 'https://openalex.org/W2355395139'], 'abstract_inverted_index': {'Modern': [0], 'generative': [1, 41, 104, 111, 135, 168], 'models': [2, 136, 169], 'are': [3], 'usually': [4], 'designed': [5], 'to': [6, 36, 46, 54, 71, 137, 165], 'match': [7, 72], 'target': [8, 52, 74], 'distributions': [9, 53], 'directly': [10], 'in': [11, 39, 76, 85, 159], 'the': [12, 16, 26, 37, 49, 59, 67, 73, 77, 83, 87, 91, 131, 156], 'data': [13, 20, 88, 97], 'space,': [14], 'where': [15], 'intrinsic': [17], 'dimension': [18], 'of': [19, 61, 133, 145, 161], 'can': [21], 'be': [22], 'much': [23], 'lower': [24], 'than': [25], 'ambient': [27], 'dimension.': [28], 'We': [29, 43], 'argue': [30], 'that': [31], 'this': [32], 'discrepancy': [33], 'may': [34], 'contribute': [35], 'difficulties': [38], 'training': [40], 'models.': [42], 'therefore': [44], 'propose': [45], 'map': [47], 'both': [48, 86], 'generated': [50], 'and': [51, 65, 90, 98, 142, 180], 'a': [55, 62, 109, 118], 'latent': [56, 78, 92, 99, 146], 'space': [57, 89, 93], 'using': [58, 170], 'encoder': [60], 'standard': [63], 'autoencoder,': [64], 'train': [66], 'generator': [68], '(or': [69], 'decoder)': [70], 'distribution': [75], 'space.': [79], 'Specifically,': [80], 'we': [81, 107], 'enforce': [82], 'consistency': [84], 'with': [94, 117, 150], 'theoretically': [95], 'justified': [96], 'reconstruction': [100], 'losses.': [101], 'The': [102], 'resulting': [103], 'model,': [105], 'which': [106], 'call': [108], 'perceptual': [110], 'autoencoder': [112, 123], '(PGA),': [113], 'is': [114], 'then': [115], 'trained': [116], 'maximum': [119, 127], 'likelihood': [120], 'or': [121], 'variational': [122], '(VAE)': [124], 'objective.': [125], 'With': [126], 'likelihood,': [128], 'PGAs': [129, 152, 173], 'generalize': [130], 'idea': [132], 'reversible': [134], 'unrestricted': [138], 'neural': [139], 'network': [140], 'architectures': [141], 'arbitrary': [143], 'number': [144], 'dimensions.': [147], 'When': [148], 'combined': [149], 'VAEs,': [151], 'substantially': [153], 'improve': [154], 'over': [155], 'baseline': [157], 'VAEs': [158], 'terms': [160], 'sample': [162], 'quality.': [163], 'Compared': [164], 'other': [166], 'autoencoder-based': [167], 'simple': [171], 'priors,': [172], 'achieve': [174], 'state-of-the-art': [175], 'FID': [176], 'scores': [177], 'on': [178], 'CIFAR-10': [179], 'CelebA.': [181]}, 'cited_by_api_url': 'https://api.openalex.org/works?filter=cites:W2953501176', 'counts_by_year': [{'year': 2024, 'cited_by_count': 1}, {'year': 2023, 'cited_by_count': 4}, {'year': 2022, 'cited_by_count': 2}, {'year': 2021, 'cited_by_count': 4}, {'year': 2020, 'cited_by_count': 3}, {'year': 2019, 'cited_by_count': 1}], 'updated_date': '2024-12-15T06:49:45.052563', 'created_date': '2019-07-12'}