{"id":"W2187650160","doi":"","title":"Discussion of \\The Neural Autoregressive Distribution Estimator\"","year":2011,"lang":"en","type":"article","venue":"International Conference on Artificial Intelligence and Statistics","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"MNIST database; Boltzmann machine; Latent variable; Estimator; Restricted Boltzmann machine; Graphical model; Computer science; Inference; Block (permutation group theory); Gibbs sampling; Artificial intelligence; Autoregressive model; Algorithm; Mathematics; Applied mathematics; Machine learning; Artificial neural network; Statistics; Combinatorics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001246914,0.0001075091,0.0001059351,0.00003174331,0.0001273506,0.00008368474,0.0005249337,0.00003659326,0.0001080852],"category_scores_gemma":[0.000254587,0.0000625512,0.00003482369,0.00008442772,0.0002070014,0.0001834314,0.0001526701,0.0001000024,0.00001191631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000187045,"about_ca_system_score_gemma":0.00004526288,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004957494,"about_ca_topic_score_gemma":0.0000309622,"domain_scores_codex":[0.9990613,0.00007972882,0.0002703203,0.0002146542,0.0002516483,0.0001223466],"domain_scores_gemma":[0.9992332,0.00008898712,0.0001638177,0.0001975486,0.0002666652,0.00004975493],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002452623,0.00005199709,0.0001341584,0.000002111059,0.00001007482,0.000003444201,0.0004563493,0.0002312314,0.0004528033,0.8231837,0.0001770412,0.1752726],"study_design_scores_gemma":[0.00001832659,0.00009152132,0.002870646,0.00004172508,0.000006475264,0.000004212962,0.0001614839,0.7754627,0.01809029,0.2030613,0.00008946783,0.0001017906],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0007719834,0.000006146372,0.9954892,0.001150282,0.0008699491,0.00008239046,0.0001302941,0.00001470806,0.001485044],"genre_scores_gemma":[0.9750043,0.00001803107,0.02475101,0.00006065106,0.0000432637,0.000004950076,0.00001154296,0.000003288037,0.0001029734],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9742323,"threshold_uncertainty_score":0.2550764,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.107768844503171,"score_gpt":0.3080884556807018,"score_spread":0.2003196111775308,"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."}}