{"id":"W2294059674","doi":"","title":"Maxout Networks","year":2013,"lang":"en","type":"article","venue":"","topic":"Machine Learning and Data Classification","field":"Computer Science","cited_by":607,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"MNIST database; Dropout (neural networks); Leverage (statistics); Computer science; Benchmark (surveying); Artificial intelligence; Machine learning; Set (abstract data type); Deep learning","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":[0.002514733,0.001766477,0.001164197,0.0005750207,0.0005423483,0.001290798,0.003133566,0.001791055,0.005484845],"category_scores_gemma":[0.006042056,0.0006803698,0.0007980711,0.0006438967,0.001071575,0.004107276,0.001783605,0.002074238,0.001357966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001115644,"about_ca_system_score_gemma":0.0008306282,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001738528,"about_ca_topic_score_gemma":0.003255449,"domain_scores_codex":[0.9991898,0.0003183031,0.00003393152,0.0002463771,0.0001298606,0.00008173118],"domain_scores_gemma":[0.9984564,0.0008680179,0.0001455295,0.0002615415,0.0001881405,0.00008034359],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000430395,0.0001486841,0.001589289,0.0002707732,0.0001402465,0.0001669142,0.0001642873,0.7081127,0.004056572,0.08421587,0.01375791,0.1869463],"study_design_scores_gemma":[0.00000987064,0.00004570771,0.00006591673,0.00001455465,0.00001323863,0.00002397659,0.000007351793,0.9674914,0.001270789,0.02920766,0.001842187,0.000007364311],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01312935,0.0006179748,0.9797759,0.0005973642,0.0001148012,0.00005601552,0.000353159,0.001124815,0.004230666],"genre_scores_gemma":[0.7397595,0.0008603594,0.2366387,0.001303751,0.0002429455,0.000452723,0.001500534,0.0004196918,0.01882187],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005484845,"threshold_uncertainty_score":0.01834863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007273672343883744,"score_gpt":0.2085233568947044,"score_spread":0.2012496845508207,"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."}}