{"id":"W2952940861","doi":"10.48550/arxiv.1502.02476","title":"An Infinite Restricted Boltzmann Machine","year":2015,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Restricted Boltzmann machine; Boltzmann machine; Limit (mathematics); Computer science; Boltzmann constant; Function (biology); Layer (electronics); Artificial intelligence; Energy (signal processing); Algorithm; Mathematics; Deep learning; Statistics; Physics; Mathematical analysis","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003034617,0.0004015849,0.0004079936,0.0003079124,0.0001832461,0.0002848616,0.002530741,0.0003233304,0.00003616786],"category_scores_gemma":[0.00006505935,0.0004366502,0.0001739423,0.0008052766,0.0001036929,0.0007973499,0.001823347,0.0006291578,0.0001161492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000168708,"about_ca_system_score_gemma":0.0003312427,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004980446,"about_ca_topic_score_gemma":0.0001051667,"domain_scores_codex":[0.9975304,0.0004040873,0.0002325605,0.001271904,0.0001355468,0.0004255192],"domain_scores_gemma":[0.9969482,0.00007792855,0.0002691597,0.001927243,0.0003843225,0.0003930762],"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":[0.00004014505,0.000151627,0.001072259,0.0000172388,0.000102037,0.0003857318,0.0002291909,0.9713055,0.0001080384,0.02142356,0.003123714,0.002040882],"study_design_scores_gemma":[0.0004178957,0.0001093053,0.00107112,0.00003117699,0.00005543144,0.000003113133,0.00002566754,0.9716077,0.0001346175,0.02267076,0.003353184,0.0005200105],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03987166,0.0001481772,0.9534777,0.0001380578,0.000921621,0.0002599683,0.00003279439,0.0003745908,0.00477543],"genre_scores_gemma":[0.9910963,0.0001424016,0.007215291,0.0001582448,0.0002518215,8.835572e-7,0.00006724151,0.00002365347,0.00104412],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9512247,"threshold_uncertainty_score":0.9998085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07306386073334857,"score_gpt":0.1997904794026079,"score_spread":0.1267266186692593,"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."}}