{"id":"W3049639017","doi":"10.1162/neco_a_01311","title":"A Predictive-Coding Network That Is Both Discriminative and Generative","year":2020,"lang":"en","type":"article","venue":"Neural Computation","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"MNIST database; Discriminative model; Artificial neural network; Computer science; Artificial intelligence; Predictive coding; Generative grammar; Reciprocal; Backpropagation; Hierarchy; Coding (social sciences); Nonlinear system; Machine learning; Generative model; 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":[0.0006917716,0.0005409244,0.0005173679,0.000437721,0.0005356371,0.001028172,0.001200143,0.001137201,0.003691076],"category_scores_gemma":[0.003260623,0.0003710795,0.0003887062,0.0004849396,0.001499562,0.001649025,0.001431797,0.001547548,0.0008804846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006837633,"about_ca_system_score_gemma":0.000885143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001956406,"about_ca_topic_score_gemma":0.002697879,"domain_scores_codex":[0.9997143,0.00004142706,0.00001198628,0.0001122588,0.0000810191,0.00003885445],"domain_scores_gemma":[0.9992154,0.0002728829,0.00007061312,0.0001987757,0.0001572095,0.00008503447],"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":[0.000201942,0.0001236686,0.00185998,0.0001591792,0.00006969291,0.0003191095,0.0002814127,0.3408939,0.05085125,0.3058138,0.007014696,0.2924114],"study_design_scores_gemma":[0.0000125058,0.00003250313,0.0001951892,0.00001322773,0.0000153776,0.0001243577,0.00001343571,0.9428847,0.005011469,0.04904127,0.002641441,0.00001448334],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03924279,0.0001945999,0.9417279,0.0007791406,0.0001321555,0.00005806953,0.0001094031,0.001004215,0.01675166],"genre_scores_gemma":[0.7655774,0.0001900977,0.2209666,0.0005295849,0.00009236764,0.00009512818,0.0002407297,0.0002220671,0.0120862],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003691076,"threshold_uncertainty_score":0.01234788,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06931802813719797,"score_gpt":0.2750890375557876,"score_spread":0.2057710094185896,"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."}}