Neural-PCA
This repository contains the PyTorch implementation of Neural-PCA proposed in the IJCAI2022 paper:
Shen Li, Bryan Hooi. Neural PCA for Flow-Based Representation Learning. IJCAI2022
Empirical Results
Neural-PCA provides better architectural inductive bias for normalizing flow, which leads to better data representation without compromising generative performance.
Requirements
- python==3.6.0
- torch==1.6.0
- torchvision==0.7.0
- tensorboard==2.4.0
Getting Started
Training
Citation
@article{li2022neural,
title={Neural PCA for Flow-Based Representation Learning},
author={Li, Shen and Hooi, Bryan},
journal={IJCAI 2022},
year={2022}
}