Overview

Pytorch code to reproduce the results of the clustring algorithms: Information Maximizing Self-Augmented Training with Virtual Adversarial Training (IMSAT-Vat) and Deep Regularized Information Maximization (Deep_RIM) proposed in [1]. The adoped data set is MNIST. The implementation in [1] is based on Chainer.

[1] Weihua Hu, Takeru Miyato, Seiya Tokui, Eiichi Matsumoto and Masashi Sugiyama. Learning Discrete Representations via Information Maximizing Self-Augmented Training. In ICML, 2017. Available at http://arxiv.org/abs/1702.08720

Dependencies

Package version used: python 3.6.6 torch 0.4.1

Train model: To run Deep_RIM $ python Deep_RIM.py

To run IMSAT $ python Imsat.py