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Models/Pi Model

Pi Model

Reported on 6 benchmarks across 4 tasks · 2 papers · 2 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Computer Vision2 results

Image ClassificationonCIFAR-10, 4000 Labels
Percentage error· 2016-10-07
12.16
best: 3.96 (SimMatch)
SOTA
Temporal Ensembling for Semi-Supervised Learning arXiv:1610.02242
Semi-Supervised Image ClassificationonCIFAR-10, 4000 Labels
Percentage error· 2016-10-07
12.16
best: 3.96 (SimMatch)
SOTA
Temporal Ensembling for Semi-Supervised Learning arXiv:1610.02242

Natural Language Processing2 results

Text ClassificationonYahoo! Answers (800 Labels)
Accuracy (%)· 2019-12-30
56.3
best: 57.9 (FlowGMM)
Semi-Supervised Learning with Normalizing Flows arXiv:1912.13025
Text ClassificationonAG News (200 Labels)
Accuracy (%)· 2019-12-30
80.2
best: 82.1 (FlowGMM)
Semi-Supervised Learning with Normalizing Flows arXiv:1912.13025

Methodology2 results

ClassificationonYahoo! Answers (800 Labels)
Accuracy (%)· 2019-12-30
56.3
best: 57.9 (FlowGMM)
Semi-Supervised Learning with Normalizing Flows arXiv:1912.13025
ClassificationonAG News (200 Labels)
Accuracy (%)· 2019-12-30
80.2
best: 82.1 (FlowGMM)
Semi-Supervised Learning with Normalizing Flows arXiv:1912.13025