Tensorflow implementation of Synthetic Gradient for RNN (LSTM)
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Updated
Jan 30, 2018 - Python
Tensorflow implementation of Synthetic Gradient for RNN (LSTM)
Architecture search using unsupervised learning with symmetric auto-encoders and QLearning in PyTorch
Implementation of "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks"
Code for "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks"
Meta-learning by applying MAML to an inner variational auto-encoder to automatically learn generative models with few examples
Implementation of SNAIL(A Simple Neural Attentive Meta-Learner) with Gluon
This repository contains the implementation for the paper - Exploration via Hierarchical Meta Reinforcement Learning.
Experimenting with different ways of calculating metafeatures and embedding datasets
Version 2 of Reconstruction-Style
Meta learning is a subfield of machine learning where automatic learning algorithms are applied on metadata about machine learning experiments.
A toy project on a Automated Machine Learning technique called linear meta learning
This project consists of the classification of brain's signals by using AI (meta learning) in order to developing brain- computer interface
A PyTorch implementation of OpenAI's REPTILE algorithm
Elegant PyTorch implementation of paper Model-Agnostic Meta-Learning (MAML)
Very simple MAML-like metalearning baseline
A repository contains research papers related to RL, NLP, CV, ML, DL, Meta Learning, Incremental, etc.
Meta learning for few-shot learning task on miniImagenet, using ResNet-18 as a feature extractor. Project for CMPT 726
Add a description, image, and links to the metalearning topic page so that developers can more easily learn about it.
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