Commit 893cd5ae authored by Yaoyao Liu's avatar Yaoyao Liu
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Update README.md

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[![PyTorch](https://img.shields.io/badge/pytorch-1.2.0-%237732a8?style=flat-square)](https://pytorch.org/)
[![CodeFactor](https://img.shields.io/codefactor/grade/github/yaoyao-liu/E3BM/inductive?style=flat-square)](https://www.codefactor.io/repository/github/yaoyao-liu/e3bm)
[[Paper](https://arxiv.org/pdf/1904.08479)] [[Project Page](https://e3bm.yyliu.net/)]
[[Paper](https://arxiv.org/pdf/1904.08479)] [[GitHub](https://github.com/yaoyao-liu/e3bm)] [[Project Page](https://e3bm.yyliu.net/)]
This repository contains the PyTorch implementation for the Paper "[An Ensemble of Epoch-wise Empirical Bayes for Few-shot Learning](https://arxiv.org/pdf/1904.08479)". If you have any questions on this repository or the related paper, feel free to [create an issue](https://gitlab.mpi-klsb.mpg.de/yaoyaoliu/e3bm/-/issues/new) or [send me an email](mailto:yaoyao.liu+gitlab@mpi-inf.mpg.de).
This repository contains the PyTorch implementation for the Paper "[An Ensemble of Epoch-wise Empirical Bayes for Few-shot Learning](https://arxiv.org/pdf/1904.08479)". If you have any questions on this repository or the related paper, feel free to [create an issue](https://github.com/yaoyao-liu/E3BM/issues/new) or [send me an email](mailto:yaoyao.liu+github@mpi-inf.mpg.de).
#### Summary
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#### Download resources
All the datasets and pre-trained models will be downloaded automatically.
You may also download the resources on Google Drive using the following links:
You may also download the resources on Google Drive/百度网盘 using the following links:
<br>
Dataset: [miniImageNet](https://drive.google.com/file/d/1vv3m14kusJcRpCsG-brG_Xk9MnetY9Bt/view?usp=sharing), and [tieredImageNet](https://drive.google.com/file/d/1T-4NVTSa5T6CXKSRbymYLnWp_OrtF-mo/view?usp=sharing)
<br>
Pre-trained models: [Google Drive](https://drive.google.com/file/d/13pzlvn9s4psbZlGpIsYCi9fwQnWeSIkP/view?usp=sharing)
Pre-trained models: \[[Google Drive](https://drive.google.com/file/d/13pzlvn9s4psbZlGpIsYCi9fwQnWeSIkP/view?usp=sharing)\] \[[百度网盘](https://pan.baidu.com/s/1bjbPKmhztHrofWlkFKCJPg)\] 提取码: 2e7p
<br>
Meta-trained checkpoints: \[[Google Drive](https://drive.google.com/drive/folders/17qTMpovfgEV6mRi8M4FkMYLIfBm3smgc?usp=sharing)\] \[[百度网盘](https://pan.baidu.com/s/1POKnhd-EmfiI7388eb7yVA)\] 提取码: wc7g
<br>
Meta-trained checkpoints: [Google Drive](https://drive.google.com/drive/folders/17qTMpovfgEV6mRi8M4FkMYLIfBm3smgc?usp=sharing)
### Transductive Experiments
See the transductive setting experiments in this branch: <https://gitlab.mpi-klsb.mpg.de/yaoyaoliu/e3bm/-/tree/transductive>.
See the transductive setting experiments in this branch: <https://github.com/yaoyao-liu/E3BM/tree/transductive>.
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