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Models/AL-MML

AL-MML

Reported on 6 benchmarks across 2 tasks · 1 paper · 6 SOTA

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

Methodology6 results

Continual LearningonCIFAR-100
Average Accuracy· 2020-04-23
42.62
best: 88.08 (PriViLege)
SOTA
Few-Shot Class-Incremental Learning arXiv:2004.10956
Continual Learningonmini-Imagenet
Average Accuracy· 2020-04-23
39.64
best: 95.27 (PriViLege)
SOTA
Few-Shot Class-Incremental Learning arXiv:2004.10956
Continual Learningonmini-Imagenet
Last Accuracy · 2020-04-23
24.42
best: 96.24 (CoACT)
SOTA
Few-Shot Class-Incremental Learning arXiv:2004.10956
Class Incremental LearningonCIFAR-100
Average Accuracy· 2020-04-23
42.62
best: 88.08 (PriViLege)
SOTA
Few-Shot Class-Incremental Learning arXiv:2004.10956
Class Incremental Learningonmini-Imagenet
Average Accuracy· 2020-04-23
39.64
best: 95.27 (PriViLege)
SOTA
Few-Shot Class-Incremental Learning arXiv:2004.10956
Class Incremental Learningonmini-Imagenet
Last Accuracy · 2020-04-23
24.42
best: 96.24 (CoACT)
SOTA
Few-Shot Class-Incremental Learning arXiv:2004.10956