An implementation of Model Agnostic Meta Learning (MAML) for few shot supervised image classification.
This repository contains the code for the paper: Utilizing the Untapped Potential of Indirect Encoding for Neural Networks with Meta Learning
Prototypical Networks on Omniglot Dataset for Few-Shot Classification
Few-shot learning of deep convolutional models
Final Project from the course "Deep Learning" @ Data Science & Scientific Computing, University of Trieste, year 2020/2021, written in Python using PyTorch.
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