One Shot Learning using Memory-Augmented Neural Networks in Tensorflow

Tensorflow implementation of the paper One-shot Learning with Memory-Augmented Neural Networks.

Current Progress of Implementation:

• Utility Functions:
  • Image Handler
  • Metrics (Accuracy)
  • Similarities (Cosine Similarity)
• LSTM Controller and Memory Unit
• Batch Generators
• Omniglot Tester Code
• Unsupervised Feature Learning through Autoencoders
• Cattle/New Born Recognition

The benchmark dataset is Omniglot dataset. All the datasets should be placed in the data/ folder.

Adam Santoro, Sergey Bartunov, Matthew Botvinick, Daan Wierstra, Timothy Lillicrap, One-shot Learning with Memory-Augmented Neural Networks, [arXiv]