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SotA/Computer Vision/Image Classification/OMNIGLOT - 1-Shot, 5-way

Image Classification on OMNIGLOT - 1-Shot, 5-way

Metric: Accuracy (higher is better)

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#Model↕Accuracy▼Extra DataPaperDate↕Code
1MC2+99.97NoMeta-Curvature2019-02-09Code
2Relation Net99.6NoLearning to Compare: Relation Network for Few-Sh...2017-11-16Code
3MT-net99.5NoGradient-Based Meta-Learning with Learned Layerw...2018-01-17Code
4iMAML, Hessian-Free99.5NoMeta-Learning with Implicit Gradients2019-09-10Code
5MAML++99.47NoHow to train your MAML2018-10-22Code
6Hyperbolic ProtoNet99NoHyperbolic Image Embeddings2019-04-03Code
7Prototypical Networks98.8NoPrototypical Networks for Few-shot Learning2017-03-15Code
8MAML98.7NoModel-Agnostic Meta-Learning for Fast Adaptation...2017-03-09Code
9VAMPIRE98.43NoUncertainty in Model-Agnostic Meta-Learning usin...2019-07-27Code
10adaCNN (DF)98.42NoRapid Adaptation with Conditionally Shifted Neur...2017-12-28-
11ConvNet with Memory Module98.4NoLearning to Remember Rare Events2017-03-09Code
12Matching Nets98.1NoMatching Networks for One Shot Learning2016-06-13Code
13Neural Statistician98.1NoTowards a Neural Statistician2016-06-07Code
14APL97.9NoAdaptive Posterior Learning: few-shot learning w...2019-02-07Code
15Reptile + Transduction97.68NoOn First-Order Meta-Learning Algorithms2018-03-08Code