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Models/SIB

SIB

Reported on 8 benchmarks across 2 tasks · 1 paper · 2 SOTA

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

Computer Vision8 results

Image ClassificationonCIFAR-FS 5-way (1-shot)
Accuracy· 2020-04-27
80
best: 89.94 (PT+MAP+SF+SOT (transductive))
SOTA
Empirical Bayes Transductive Meta-Learning with Synthetic Gradients arXiv:2004.12696
Few-Shot Image ClassificationonCIFAR-FS 5-way (1-shot)
Accuracy· 2020-04-27
80
best: 89.94 (PT+MAP+SF+SOT (transductive))
SOTA
Empirical Bayes Transductive Meta-Learning with Synthetic Gradients arXiv:2004.12696
Image ClassificationonMini-Imagenet 5-way (5-shot)
Accuracy· 2020-04-27
79.2
best: 98.72 (SgVA-CLIP)
Empirical Bayes Transductive Meta-Learning with Synthetic Gradients arXiv:2004.12696
Image ClassificationonMini-Imagenet 5-way (1-shot)
Accuracy· 2020-04-27
70
best: 97.95 (SgVA-CLIP)
Empirical Bayes Transductive Meta-Learning with Synthetic Gradients arXiv:2004.12696
Image ClassificationonCIFAR-FS 5-way (5-shot)
Accuracy· 2020-04-27
85.3
best: 93.5 (CAML [Laion-2b])
Empirical Bayes Transductive Meta-Learning with Synthetic Gradients arXiv:2004.12696
Few-Shot Image ClassificationonMini-Imagenet 5-way (5-shot)
Accuracy· 2020-04-27
79.2
best: 98.72 (SgVA-CLIP)
Empirical Bayes Transductive Meta-Learning with Synthetic Gradients arXiv:2004.12696
Few-Shot Image ClassificationonMini-Imagenet 5-way (1-shot)
Accuracy· 2020-04-27
70
best: 97.95 (SgVA-CLIP)
Empirical Bayes Transductive Meta-Learning with Synthetic Gradients arXiv:2004.12696
Few-Shot Image ClassificationonCIFAR-FS 5-way (5-shot)
Accuracy· 2020-04-27
85.3
best: 93.5 (CAML [Laion-2b])
Empirical Bayes Transductive Meta-Learning with Synthetic Gradients arXiv:2004.12696