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Few Shot Image Classification On Omniglot 1 2

Metrics

Accuracy

Results

Performance results of various models on this benchmark

Model Name
Accuracy
Paper TitleRepository
iMAML, Hessian-Free99.50Meta-Learning with Implicit Gradients
Matching Nets98.1Matching Networks for One Shot Learning
Relation Net99.6Learning to Compare: Relation Network for Few-Shot Learning
MAML++99.47How to train your MAML
MAML98.7Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
adaCNN (DF)98.42Rapid Adaptation with Conditionally Shifted Neurons-
VAMPIRE98.43Uncertainty in Model-Agnostic Meta-Learning using Variational Inference
DCN499.8%Decoder Choice Network for Meta-Learning
Prototypical Networks98.8Prototypical Networks for Few-shot Learning
MT-net99.5Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace
ConvNet with Memory Module98.4Learning to Remember Rare Events
APL97.9Adaptive Posterior Learning: few-shot learning with a surprise-based memory module
MC2+99.97Meta-Curvature
Hyperbolic ProtoNet99.0Hyperbolic Image Embeddings
Neural Statistician98.1Towards a Neural Statistician
Reptile + Transduction97.68On First-Order Meta-Learning Algorithms
DCN6-E99.92%Decoder Choice Network for Meta-Learning
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Few Shot Image Classification On Omniglot 1 2 | SOTA | HyperAI