A PyTorch Library for Meta-learning Research
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Updated
Jun 7, 2024 - Python
A PyTorch Library for Meta-learning Research
Collections of robotics environments geared towards benchmarking multi-task and meta reinforcement learning
TorchOpt is an efficient library for differentiable optimization built upon PyTorch.
Simple (but often Strong) Baselines for POMDPs in PyTorch, ICML 2022
Re-implementations of SOTA RL algorithms.
"모두를 위한 메타러닝" 책에 대한 코드 저장소
Code for FOCAL Paper Published at ICLR 2021
Implementation of our paper "Meta Reinforcement Learning with Task Embedding and Shared Policy"
Repo to reproduce the First-Explore paper results
A curated list of awesome Meta Reinforcement Learning
Implementation of Model-Agnostic Meta-Learning (MAML) applied on Reinforcement Learning problems in TensorFlow 2.
Official Implementation for "In-Context Reinforcement Learning for Variable Action Spaces"
Official Implementation for "In-Context Reinforcement Learning from Noise Distillation"
My notes on reinforcement learning papers
Implementation of BIMRL: Brain Inspired Meta Reinforcement Learning - Roozbeh Razavi et al. (IROS 2022)
🌈 The code and methods offered in Awesome-META+: https://wangjingyao07.github.io/Awesome-Meta-Learning-Platform/
Learning to reinforcement learn for Neural Architecture Search
Toy meta-RL environments for testing algorithms implementations
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