This repository contains the code for the paper: Utilizing the Untapped Potential of Indirect Encoding for Neural Networks with Meta Learning

An implementation of Model Agnostic Meta Learning (MAML) for few shot supervised image classification.

Prototypical Networks on Omniglot Dataset for Few-Shot Classification

Final Project from the course "Deep Learning" @ Data Science & Scientific Computing, University of Trieste, year 2020/2021, written in Python using PyTorch.

Few-shot learning of deep convolutional models