{"id":"W1886634424","doi":"10.48550/arxiv.1206.6445","title":"Deep Lambertian Networks","year":2012,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Albedo (alchemy); Artificial intelligence; Computer science; Invariant (physics); Generative model; Computer vision; Prior probability; Surface (topology); Latent variable; Representation (politics); Photometric stereo; Object (grammar); Pattern recognition (psychology); Image (mathematics); Generative grammar; Mathematics; Geometry; Bayesian probability","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005771354,0.0009414617,0.0007569113,0.000550966,0.0002853315,0.0009129951,0.001530825,0.001324005,0.003067462],"category_scores_gemma":[0.00183319,0.0005526827,0.0007056137,0.0005920404,0.001002636,0.001474014,0.00119713,0.002075754,0.0009963285],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001127849,"about_ca_system_score_gemma":0.000475633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004355373,"about_ca_topic_score_gemma":0.00564551,"domain_scores_codex":[0.999666,0.00008110084,0.000009804815,0.0001158757,0.0000789409,0.00004834732],"domain_scores_gemma":[0.9995077,0.0002321581,0.00006032612,0.00009841214,0.00007184155,0.0000296349],"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":[0.00008833867,0.00004293466,0.0005203928,0.00006405891,0.00007405233,0.00006607357,0.00005221559,0.8497685,0.005926006,0.03830597,0.003837113,0.1012543],"study_design_scores_gemma":[0.000001880203,0.000005798574,0.00005578134,0.000003165307,0.000003231883,0.0000084643,0.000002451118,0.9849332,0.0005264269,0.01402117,0.0004360038,0.000002489848],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02272276,0.0008226215,0.9693124,0.0006724749,0.00008221834,0.00002637693,0.000207667,0.001392146,0.004761293],"genre_scores_gemma":[0.8103024,0.001219197,0.1669694,0.0006475343,0.0001644656,0.0001133077,0.0008921868,0.0002929503,0.0193984],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004355373,"threshold_uncertainty_score":0.01026171,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05038077141648527,"score_gpt":0.171328178623764,"score_spread":0.1209474072072787,"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."}}