{"id":"W4383817322","doi":"10.1007/s42484-023-00112-5","title":"Quantum autoencoders for communication-efficient cloud computing","year":2023,"lang":"en","type":"article","venue":"Quantum Machine Intelligence","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"Perimeter Institute","funders":"","keywords":"Computer science; Quantum computer; Cloud computing; Computation; Qubit; Theoretical computer science; Quantum; Quantum information; Distributed computing; Computer engineering; Computational science; Parallel computing; Algorithm; Operating system; Physics","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":[0.0006095858,0.0003066626,0.0006905608,0.0002400285,0.0004617469,0.0009051705,0.000967638,0.000734923,0.003214743],"category_scores_gemma":[0.002152262,0.0002482467,0.0002682687,0.0005443562,0.0007893976,0.00163459,0.001091082,0.001564699,0.000521108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000779378,"about_ca_system_score_gemma":0.0009764108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002734447,"about_ca_topic_score_gemma":0.004098034,"domain_scores_codex":[0.9996498,0.00009260319,0.00001553697,0.00005191814,0.0001285477,0.00006166632],"domain_scores_gemma":[0.9994153,0.0002593628,0.00003359121,0.0001329056,0.000122128,0.00003676758],"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":[0.0001829933,0.0001411812,0.0004591395,0.0001378905,0.00007230773,0.00008404154,0.00006373083,0.5194976,0.008891191,0.3440867,0.01123694,0.1151462],"study_design_scores_gemma":[0.000003837125,0.000006966184,0.00005214494,0.000004770819,0.000003292231,0.000007159417,0.000005207936,0.963911,0.0009974241,0.03416121,0.0008436301,0.000003421381],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04417645,0.001983519,0.9398631,0.001549203,0.0004073297,0.00005548905,0.0001524792,0.0006868702,0.01112547],"genre_scores_gemma":[0.8781698,0.001097281,0.1123234,0.0003395836,0.0002259866,0.00006751292,0.0001560178,0.000118795,0.007501618],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003214743,"threshold_uncertainty_score":0.01075441,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02403228643664927,"score_gpt":0.297407939043095,"score_spread":0.2733756526064458,"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."}}