{"id":"W4379522721","doi":"10.21428/594757db.4cec07db","title":"PAC-Bayesian Learning of Aggregated Binary Activated Neural Networks with Probabilities over Representations","year":2023,"lang":"en","type":"article","venue":"","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Artificial neural network; Binary number; Generalization; Probabilistic logic; Computer science; Differentiable function; Bayesian network; Expression (computer science); Artificial intelligence; Stochastic neural network; Probability distribution; Binary classification; Recurrent neural network; 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":[0.002837239,0.001346584,0.001576976,0.0008761482,0.0005491763,0.001963045,0.002286862,0.001804452,0.00319167],"category_scores_gemma":[0.01429172,0.001156199,0.0007741768,0.001115064,0.001824129,0.00462267,0.002715027,0.003176215,0.0005861745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001968543,"about_ca_system_score_gemma":0.001570859,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003687734,"about_ca_topic_score_gemma":0.004872175,"domain_scores_codex":[0.9986463,0.0004951251,0.00006166648,0.000322893,0.0003296823,0.0001443505],"domain_scores_gemma":[0.995645,0.002877544,0.0004241852,0.0003407875,0.000541934,0.0001705326],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00007895783,0.00004582498,0.0005065062,0.000098408,0.00005286317,0.0000691215,0.0001157264,0.8112621,0.001397048,0.1334823,0.001472294,0.0514187],"study_design_scores_gemma":[0.000002991647,0.000008842941,0.00005021289,0.000009702701,0.000004540107,0.000008318193,0.00000378164,0.9539,0.0003267361,0.04546401,0.0002168888,0.000003920025],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009076751,0.0001302494,0.9890208,0.0002192272,0.00001735865,0.0000227014,0.00004468911,0.0001796369,0.001288699],"genre_scores_gemma":[0.6650202,0.0006088607,0.3237733,0.000406315,0.0001637894,0.0003485782,0.0005216317,0.0003237986,0.008833575],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003687734,"threshold_uncertainty_score":0.01500493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01467611982522968,"score_gpt":0.2546440151481341,"score_spread":0.2399678953229044,"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."}}