Meta Learning / Learning to Learn / One Shot Learning / Few Shot Learning
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Updated
Nov 26, 2018
Meta Learning / Learning to Learn / One Shot Learning / Few Shot Learning
Code for "Learning Inductive Biases with Simple Neural Networks" (Feinman & Lake, 2018).
Learning to learn by gradient descent by gradient descent, Andrychowicz et al., NIPS 2016
"Learning to learn by gradient descent by gradient descent "by PyTorch -- a simple re-implementation.
Learnig Go with coding exercises
Chrome extension to create tasks based on the spaced repetition concept
A clean, lightweight and modularized PyTorch meta-learning library.
Learning to Learn: Gradient-free Optimization framework
[CVPR 2020] L2-GCN: Layer-Wise and Learned Efficient Training of Graph Convolutional Networks
[NeurIPS 2020 Spotlight Oral] "Training Stronger Baselines for Learning to Optimize", Tianlong Chen*, Weiyi Zhang*, Jingyang Zhou, Shiyu Chang, Sijia Liu, Lisa Amini, Zhangyang Wang
pytorch implementation of Optimization as a Model for Few-shot Learning
A modular toolbox for meta-learning research with a focus on speed and reproducibility.
Open-L2O: A Comprehensive and Reproducible Benchmark for Learning to Optimize Algorithms
Task Generation Scheme for the Meta-Unsupervised Algorithm
Personalizing Dialogue Agents via Meta-Learning
Optim4RL is a Jax framework of learning to optimize for reinforcement learning.
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