Few-Shot Learning papers and notes |
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General
Wang et al - 2020 - Generalizing from a Few Examples: A Survey on Few-Shot Learning
Chen et al - 2020 - A Closer Look at Few-shot Classification
Gidaris et al - 2019 - Boosting Few-Shot Visual Learning with Self-Supervision
Ren et al - 2018 - Meta-Learning for Semi-Supervised Few-Shot Classification
Meta Learning
Huisman et al - 2021 - A Survey of Deep Meta-Learning
Hospedales et al - 2020 - Meta-Learning in Neural Networks A Survey
Koch et al - Siamese Neural Networks for One-shot Image Recognition
: SiameseNet
Vinyals et al - 2017 - Matching Networks for One Shot Learning
: MatchingNet
Snell et al - 2017 - Prototypical Networks for Few-shot Learning
: ProtoNet
Sung et al - 2018 - Learning to Compare Relation Network for Few-Shot Learning
: RelationNet
Santoro et al - Meta-Learning with Memory-Augmented Neural Network
: MANN
Ravi and Larochelle - 2017 - OPTIMIZATION AS A MODEL FOR FEW-SHOT LEARNING
: LSTM Meta-Learner
Finn et al - 2017 - Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
: MAML
papers/Antoniou et al - 2019 - How to train your MAML
: MAML++
Li et al - 2017 - Meta-SGD Learning to Learn Quickly for Few-Shot Learning
: Meta-SGD
Nichol and Schulman - Reptile a Scalable Metalearning Algorithm
: Reptile
Rusu et al - 2019 - Meta-Learning with Latent Embedding Optimization
: LEO
Andrychowicz et al - 2016 - Learning to learn by gradient descent by gradient descent
Mishra et al - 2018 - A Simple Neural Attentive Meta-Learner