{"id":"W2964121937","doi":"","title":"Bayesian Model-Agnostic Meta-Learning","year":2018,"lang":"en","type":"article","venue":"","topic":"Domain Adaptation and Few-Shot Learning","field":"Computer Science","cited_by":204,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research; Université de Montréal","funders":"","keywords":"Artificial intelligence; Computer science; Reinforcement learning; Machine learning; Overfitting; Meta learning (computer science); Robustness (evolution); Bayesian probability; Bayesian inference; Inference; Learning classifier system; Artificial neural network","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":[0.003031506,0.001827761,0.002689728,0.001400432,0.0006132465,0.001982221,0.004479168,0.002269593,0.002170046],"category_scores_gemma":[0.009067141,0.00137163,0.001991501,0.001084664,0.001503389,0.003702847,0.002687339,0.003581056,0.0007938713],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001389478,"about_ca_system_score_gemma":0.001583723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002312349,"about_ca_topic_score_gemma":0.003573067,"domain_scores_codex":[0.9985117,0.0004946544,0.00008442846,0.0004549124,0.0003260371,0.0001282293],"domain_scores_gemma":[0.9968814,0.00171079,0.0003259523,0.0005096844,0.0004221393,0.0001501273],"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":[0.0001080903,0.0001172447,0.0008945017,0.0001640125,0.0002948856,0.00009335049,0.0001075232,0.8799258,0.003124252,0.02206111,0.001618618,0.09149055],"study_design_scores_gemma":[0.000006270451,0.00001803853,0.00005603698,0.000009988171,0.00001336995,0.00001699859,0.000004460644,0.986864,0.0005264732,0.01220754,0.0002681446,0.000008565313],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003964446,0.0002218301,0.9946371,0.0001415572,0.00002343349,0.00002714144,0.00004976807,0.0003754273,0.0005592323],"genre_scores_gemma":[0.5975773,0.0004867057,0.3967128,0.0005652971,0.0001401313,0.0004119242,0.0005572208,0.0003784381,0.00317015],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004479168,"threshold_uncertainty_score":0.01603234,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04605557115013093,"score_gpt":0.2724186225374055,"score_spread":0.2263630513872746,"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."}}