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Matching Networks Tensorflow 2 Implementation for few-shot AD diagnosis

Matching Networks Tensorflow V2 Implementation

Introduction

This repository contains an implementation of Matching Networks in Tensorflow 2 (currently in BETA). It is specifically designed for few-shot learning of 1D data sets (e.g. flattend MNIST). However, I've added various tools for users so that they can make minor customizations (e.g. 2D/3D Convolution).

Usage

python main.py --train/test --seed=X --C=Y --K=Z

In the config.py file, you should change project_path, result_path, data_path to fit your needs.

Or you may look into MNforADNI.ipynb or Colab for a demo.

XAI Project

These works were supported by Institute for Information & Communications Technology Promotion (IITP) grant funded by the Korea government (MSIT) (No.2017-0-01779, A machine learning and statistical inference framework for explainable artificial intelligence)

  • Project Name : A machine learning and statistical inference framework for explainable artificial intelligence(의사결정 이유를 설명할 수 있는 인간 수준의 학습·추론 프레임워크 개발)

  • Managed by Ministry of Science and ICT/XAIC

  • Participated Affiliation : UNIST, Korea Univ., Yonsei Univ., KAIST, AItrics

  • Web Site : http://openXai.org

License

Apache License 2.0

Contact

Yoon, Jee Seok
[email protected]
Graduate Student,
Machine Intelligence Lab.,
Department of Brain and Cognitive Engineering,
Korea University, Seoul, South Korea