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A Pytorch implementation of ICML 2022 paper "NP-Match: When Neural Processes meet Semi-Supervised Learning"

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NP-Match

NP-Match: When Neural Processes meet Semi-Supervised Learning

Jianfeng Wang1, Thomas Lukasiewicz1, Daniela Massiceti2, Xiaolin Hu3, Vladimir Pavlovic4 and Alexandros Neophytou5

University of Oxford1, Microsoft Research2, Tsinghua University3, Rutgers University4, Microsoft5

In ICML 2022

Arxiv

Build

please run with the following command:

conda env create -f NP-Match.yml
conda activate NP-Match

Experiment

To run experiments on small datasets, e.g., CIFAR, STL-10, please run with their corresponding config files, stored in "config/npmatch/".

For example:

python npmatch.py --c config/npmatch/npmatch_cifar10_250_0.yaml

To run experiment on ImageNet, please prepare the dataset, and change the config file accordingly. Then, run with

python npmatch.py --c config/npmatch/npmatch_imagenet_100000.yaml

For the pertrained models, they were not saved. The pretrained models will be relased later once we have enough resources for training.

Citation

@inproceedings{wang2022np,
title={NP-Match: When Neural Processes meet Semi-Supervised Learning},
author={Wang, Jianfeng and Lukasiewicz, Thomas and Massiceti, Daniela and Hu, Xiaolin and Pavlovic, Vladimir and Neophytou, Alexandros},
booktitle={International Conference on Machine Learning},
pages={22919--22934},
year={2022},
organization={PMLR}
}

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A Pytorch implementation of ICML 2022 paper "NP-Match: When Neural Processes meet Semi-Supervised Learning"

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