This repository contains the implementation of the meta-learning model described in the paper "Meta-Learning with Latent Embedding Optimization" by Rusu et. al. It was posted on arXiv in July 2018 and will be presented at ICLR 2019.
The paper learns a data-dependent latent representation of model parameters and performs gradient-based meta-learning in this low-dimensional space.
The code here doesn't include the (standard) method for pre-training the data embeddings. Instead, the trained embeddings are provided.
Disclaimer: This is not an official Google product.