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HyperAI超神经

Few Shot Image Classification On Omniglot 5 2

评估指标

Accuracy

评测结果

各个模型在此基准测试上的表现结果

模型名称	Accuracy	Paper Title	Repository
Relation Net	99.8	Learning to Compare: Relation Network for Few-Shot Learning	-
Prototypical Networks	99.7	Prototypical Networks for Few-shot Learning	-
VAMPIRE	99.56%	Uncertainty in Model-Agnostic Meta-Learning using Variational Inference	-
MAML++	99.85%	How to train your MAML	-
MC2+	99.89	Meta-Curvature	-
adaCNN (DF)	99.37	Rapid Adaptation with Conditionally Shifted Neurons	-
iMAML, Hessian-Free	99.74%	Meta-Learning with Implicit Gradients	-
Neural Statistician	99.5	Towards a Neural Statistician	-
DCN6-E	99.92%	Decoder Choice Network for Meta-Learning	-
DCN4	99.89%	Decoder Choice Network for Meta-Learning	-
Hyperbolic ProtoNet	99.4	Hyperbolic Image Embeddings	-
Matching Nets	98.9	Matching Networks for One Shot Learning	-
ConvNet with Memory Module	99.6	Learning to Remember Rare Events	-
MAML	99.9	Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks	-
APL	99.9	Adaptive Posterior Learning: few-shot learning with a surprise-based memory module	-
Reptile + Transduction	99.48	On First-Order Meta-Learning Algorithms	-

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Few Shot Image Classification On Omniglot 5 2 | SOTA | HyperAI超神经