{"id":"W2563740559","doi":"10.1109/sips.2016.61","title":"Stochastic Computing Can Improve Upon Digital Spiking Neural Networks","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Stochastic computing; Computer science; Spiking neural network; Artificial neural network; Implementation; Artificial intelligence; Theoretical computer science; Distributed computing; Computer architecture","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006651915,0.0004374388,0.0003855187,0.0002655015,0.000308423,0.001106016,0.0007665415,0.0006770807,0.003863874],"category_scores_gemma":[0.004230989,0.0001806422,0.0003985493,0.0003139685,0.0007379994,0.001709545,0.001020777,0.001021495,0.0007909084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000578958,"about_ca_system_score_gemma":0.0006363798,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000910849,"about_ca_topic_score_gemma":0.001262579,"domain_scores_codex":[0.9996921,0.00005554643,0.0000247376,0.00005429853,0.0001343512,0.00003896877],"domain_scores_gemma":[0.9992205,0.0003653403,0.0000642462,0.0001659847,0.0001376257,0.00004637288],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001936004,0.0001007516,0.0009509312,0.0002359349,0.00005194396,0.0001756637,0.0001081716,0.2778673,0.03145892,0.5525095,0.003910745,0.1324365],"study_design_scores_gemma":[0.00002677087,0.0001239883,0.0002855216,0.00006312565,0.00003563115,0.0001275879,0.00002680224,0.7120107,0.009041948,0.2558807,0.02235566,0.00002161462],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09765074,0.003960919,0.8098273,0.006055973,0.0009670245,0.00006791372,0.0001686711,0.002018254,0.07928319],"genre_scores_gemma":[0.8956692,0.0027367,0.09129858,0.0009624694,0.0002456075,0.00006208728,0.0001085677,0.0002281887,0.008688663],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003863874,"threshold_uncertainty_score":0.01292592,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008618456077861082,"score_gpt":0.2065064579956692,"score_spread":0.1978880019178081,"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."}}