{"id":"W2963456073","doi":"","title":"IMEXnet - A Forward Stable Deep Neural Network","year":2019,"lang":"en","type":"article","venue":"International Conference on Machine Learning","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Robustness (evolution); Convolutional neural network; Residual; Artificial intelligence; Convolution (computer science); Generalization; Key (lock); Artificial neural network; Deep learning; Pixel; Segmentation; Sensitivity (control systems); Field (mathematics); Machine learning; 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":[0.0008134414,0.001373872,0.0007659391,0.0005982749,0.0005548212,0.001008601,0.002812689,0.001485959,0.004673369],"category_scores_gemma":[0.001849032,0.0005423979,0.0006344685,0.0006378946,0.000623912,0.001848771,0.001620763,0.001755911,0.002764924],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001153182,"about_ca_system_score_gemma":0.001551566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009484422,"about_ca_topic_score_gemma":0.01792565,"domain_scores_codex":[0.9995686,0.00005263077,0.00001773151,0.0001654938,0.0001377987,0.00005773594],"domain_scores_gemma":[0.9996093,0.00007275447,0.00003716193,0.0001114187,0.000140907,0.00002854314],"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":[0.0004937277,0.000284678,0.002095239,0.0002679744,0.0001825813,0.0002489762,0.00007379579,0.4831185,0.01692682,0.02461089,0.06417497,0.4075219],"study_design_scores_gemma":[0.00002464233,0.00005171715,0.0001914801,0.00001263259,0.00001013936,0.00003740921,0.00000832341,0.9816373,0.006175678,0.005876848,0.005962354,0.00001152961],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09186279,0.003141317,0.845516,0.001442077,0.0008480155,0.000315771,0.005900203,0.03141243,0.01956144],"genre_scores_gemma":[0.4777571,0.001110042,0.462626,0.001081362,0.0002114763,0.0005629882,0.01906368,0.001504048,0.03608321],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009484422,"threshold_uncertainty_score":0.01885843,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01932532329003506,"score_gpt":0.2746675927385407,"score_spread":0.2553422694485056,"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."}}