{"id":"W3211913805","doi":"","title":"PLUGIn: A simple algorithm for inverting generative models with recovery guarantees","year":2021,"lang":"en","type":"article","venue":"Neural Information Processing Systems","topic":"Cellular Automata and Applications","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Simple (philosophy); Computer science; Plug-in; Algorithm; Generative model; Generative grammar; Theoretical computer science; Programming language; Artificial intelligence","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":[0.001358552,0.002379693,0.001241738,0.001124912,0.0006404729,0.002182337,0.002548076,0.001996411,0.03703327],"category_scores_gemma":[0.009441149,0.001306248,0.001323472,0.000783363,0.001181775,0.003194458,0.004501584,0.003370666,0.009926216],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006356948,"about_ca_system_score_gemma":0.001402549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002302052,"about_ca_topic_score_gemma":0.005141484,"domain_scores_codex":[0.999134,0.0001995956,0.00004998316,0.0002387868,0.0002586405,0.0001188632],"domain_scores_gemma":[0.9978443,0.001270476,0.00005333099,0.0005602314,0.0001852115,0.0000864993],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001103448,0.000344306,0.001515697,0.000367686,0.0001737618,0.0008367062,0.0003133692,0.08899886,0.01537341,0.08581553,0.03964625,0.765511],"study_design_scores_gemma":[0.0001891088,0.00006101826,0.0001813214,0.00003984462,0.00003357597,0.0002513025,0.00006096056,0.8219508,0.01689462,0.147371,0.01291587,0.00005058263],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002652313,0.00005161634,0.9772314,0.0001243159,0.00008709032,0.00007160549,0.0002373419,0.01790953,0.001634881],"genre_scores_gemma":[0.1691867,0.0001079671,0.810517,0.000300112,0.0001141874,0.000388406,0.001333761,0.007520328,0.01053159],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03703327,"threshold_uncertainty_score":0.1238886,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02444358168361098,"score_gpt":0.2439302356381446,"score_spread":0.2194866539545337,"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."}}