{"id":"W2098617596","doi":"","title":"Multi-Prediction Deep Boltzmann Machines","year":2013,"lang":"en","type":"article","venue":"Neural Information Processing Systems","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":116,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Boltzmann machine; dBm; Restricted Boltzmann machine; Computer science; Train; Artificial intelligence; Inference; Probabilistic logic; Machine learning; Field (mathematics); Deep learning; Layer (electronics); Algorithm; Mathematics","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":[0.0008548553,0.0008574966,0.001022964,0.0003924999,0.0003147535,0.001304889,0.002535515,0.001523436,0.005900694],"category_scores_gemma":[0.003462315,0.000594949,0.0007508397,0.0007179138,0.0008091732,0.002499249,0.001959198,0.002610294,0.001958364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007911952,"about_ca_system_score_gemma":0.0007481053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001895817,"about_ca_topic_score_gemma":0.002944956,"domain_scores_codex":[0.9994586,0.000157622,0.00002800436,0.0001430542,0.0001366579,0.00007609413],"domain_scores_gemma":[0.9992862,0.0003470073,0.00005138863,0.0001410723,0.0001186164,0.00005570501],"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":[0.00007915122,0.00006294197,0.000943644,0.0001067479,0.00008023391,0.00007927239,0.00005684197,0.7655347,0.002858427,0.1194893,0.00548503,0.1052238],"study_design_scores_gemma":[0.000003110945,0.000007539125,0.00003699301,0.000006385376,0.000003600983,0.00001520437,0.000002147733,0.968969,0.0004626957,0.02923878,0.001249505,0.000005007444],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004108158,0.0006049104,0.9912657,0.0004041138,0.0001124034,0.00002516932,0.0001662386,0.0008216646,0.002491619],"genre_scores_gemma":[0.4627555,0.001418695,0.5180477,0.0007490594,0.000241616,0.0002743793,0.001010488,0.0005590029,0.01494353],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005900694,"threshold_uncertainty_score":0.01973975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01458786385312518,"score_gpt":0.2242547036663998,"score_spread":0.2096668398132746,"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."}}