Open-source codebase for EfficientZero, from "Mastering Atari Games with Limited Data" at NeurIPS 2021.

Last update: Jan 03, 2023

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Overview

EfficientZero (NeurIPS 2021)

Open-source codebase for EfficientZero, from "Mastering Atari Games with Limited Data" at NeurIPS 2021.

Thank you for your attention, we will open-source the codebase later. Please leave your email address here. We will send you the email once we open-source it.

Citation

If you find this repo useful, please cite our paper:

@inproceedings{ye2021mastering,
  title={Mastering Atari Games with Limited Data},
  author={Weirui Ye, and Shaohuai Liu, and Thanard Kurutach, and Pieter Abbeel, and Yang Gao},
  booktitle={NeurIPS},
  year={2021}
}

Contact

If you have any question or want to use the code, please contact [email protected] .

Acknowledgement

We appreciate the following github repos a lot for their valuable code base or datasets:

https://github.com/koulanurag/muzero-pytorch

https://github.com/werner-duvaud/muzero-general

Owner

Weirui Ye

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Open-source codebase for EfficientZero, from "Mastering Atari Games with Limited Data" at NeurIPS 2021.

Related tags

Overview

EfficientZero (NeurIPS 2021)

Citation

Contact

Acknowledgement

Owner

Weirui Ye

VGG16 model-based classification project about brain tumor detection.

U2-Net: Going Deeper with Nested U-Structure for Salient Object Detection

Embeddinghub is a database built for machine learning embeddings.

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Code and Data for NeurIPS2021 Paper "A Dataset for Answering Time-Sensitive Questions"

FTIR-Deep Learning - FTIR Deep Learning With Python

Object detection evaluation metrics using Python.

for taichi voxel-challange event

GANfolk: Using AI to create portraits of fictional people to sell as NFTs

Realtime micro-expression recognition using OpenCV and PyTorch

Swapping face using Face Mesh with TensorFlow Lite

Python package for multiple object tracking research with focus on laboratory animals tracking.

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Learning Representational Invariances for Data-Efficient Action Recognition

Rainbow is all you need! A step-by-step tutorial from DQN to Rainbow

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