{"id":"W2135181320","doi":"","title":"The Neural Autoregressive Distribution Estimator","year":2011,"lang":"en","type":"article","venue":"Edinburgh Research Explorer (University of Edinburgh)","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":431,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Estimator; Autoregressive model; Conditional probability distribution; Joint probability distribution; Autoencoder; Restricted Boltzmann machine; Computer science; Boltzmann machine; Marginal distribution; Probability distribution; Mathematics; Applied mathematics; Algorithm; Artificial intelligence; Artificial neural network; Statistics; Random variable","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002392422,0.0007539058,0.001058377,0.000900119,0.000300879,0.001038835,0.002129046,0.001223466,0.002448722],"category_scores_gemma":[0.007470172,0.0005805134,0.0008341856,0.0009150426,0.0009323037,0.002426693,0.001136917,0.002729147,0.001277042],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008806998,"about_ca_system_score_gemma":0.001043021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003281384,"about_ca_topic_score_gemma":0.003717837,"domain_scores_codex":[0.9989576,0.0004241977,0.00003838381,0.0002381838,0.0002620314,0.00007965128],"domain_scores_gemma":[0.9978739,0.001445327,0.0001930857,0.000236764,0.0002048021,0.00004604896],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008540467,0.00007142853,0.001986007,0.0001333179,0.0001450916,0.0001131895,0.00007903071,0.6082481,0.00339297,0.2195929,0.006793341,0.1593593],"study_design_scores_gemma":[0.000005388011,0.000009174515,0.0001702044,0.00001139491,0.00000952297,0.00003471648,0.00000311088,0.9692981,0.0005276285,0.02828366,0.001637347,0.000009842612],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001578876,0.000238979,0.9968803,0.0001620303,0.00003371757,0.0000147412,0.00007711002,0.0002571589,0.0007571275],"genre_scores_gemma":[0.3572076,0.001657065,0.624832,0.0007829308,0.0004158207,0.0004121512,0.0009816106,0.0003290098,0.01338188],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003281384,"threshold_uncertainty_score":0.01265252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1016253428139338,"score_gpt":0.2832050384575156,"score_spread":0.1815796956435818,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}