pytorch implementation of Optimization as a Model for Few-shot Learning
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Updated
Dec 26, 2022 - Python
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.
"Learning to learn by gradient descent by gradient descent "by PyTorch -- a simple re-implementation.
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
Optim4RL is a Jax framework of learning to optimize for reinforcement learning.
Code for "Learning Inductive Biases with Simple Neural Networks" (Feinman & Lake, 2018).
A clean, lightweight and modularized PyTorch meta-learning library.
Learning to learn by gradient descent by gradient descent, Andrychowicz et al., NIPS 2016
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