PyTorch implementations of algorithms for density estimation

Last update: Dec 05, 2022

Overview

pytorch-flows

A PyTorch implementations of Masked Autoregressive Flow and some other invertible transformations from Glow: Generative Flow with Invertible 1x1 Convolutions and Density estimation using Real NVP.

For MAF, I'm getting results similar to ones reported in the paper. GLOW requires some work.

Run

python main.py --dataset POWER

Available datasets are POWER, GAS, HEPMASS, MINIBONE and BSDS300. For the moment, I removed MNIST and CIFAR10 because I have plans to add pixel-based models later.

Datasets

The datasets are taken from the original MAF repository. Follow the instructions to get them.

Tests

Tests check invertibility, you can run them as

pytest flow_test.py

Owner

Ilya Kostrikov

Post doc

GitHub Repository

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