Automated Machine Learning with scikit-learn
A PyTorch Library for Meta-learning Research
A curated list of Meta Learning papers, code, books, blogs, videos, datasets and other resources.
Learning to Learn using One-Shot Learning, MAML, Reptile, Meta-SGD and more with Tensorflow
Meta-Learning with Differentiable Convex Optimization (CVPR 2019 Oral)
PyTorch implementation of HyperNetworks (Ha et al., ICLR 2017) for ResNet (Residual Networks)
#计算机科学#A PyTorch implementation of OpenAI's REPTILE algorithm
#计算机科学#Faster and elegant TensorFlow Implementation of paper: Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Code for the NeurIPS19 paper "Meta-Learning Representations for Continual Learning"
Personalizing Dialogue Agents via Meta-Learning
#算法刷题#This repository contains the implementation for the paper - Exploration via Hierarchical Meta Reinforcement Learning.
#计算机科学#MetaTS | Time Series Forecasting using Meta Learning
Tensorflow implementation of Synthetic Gradient for RNN (LSTM)
Implementation of Jump-Start Reinforcement Learning (JSRL) with Stable Baselines3
#计算机科学#Meta learning is a subfield of machine learning where automatic learning algorithms are applied on metadata about machine learning experiments.
Generalizing to New Physical Systems via Context-Informed Dynamics Model
#计算机科学#DropClass and DropAdapt - repository for the paper accepted to Speaker Odyssey 2020