FACE-A-Normalizing-Flow-based-Cardinality-Estimator

Awesome resources on normalizing flows.

Normalizing flows in PyTorch

PyTorch implementations of algorithms for density estimation

Efficient Graph Generation with Graph Recurrent Attention Networks, Deep Generative Model of Graphs, Graph Neural Networks, NeurIPS 2019

Normalizing flows in PyTorch

[CVPR 2021 Oral] Official PyTorch implementation of Soft-IntroVAE from the paper "Soft-IntroVAE: Analyzing and Improving Introspective Variational Autoencoders"

[NeurIPS-2023] Annual Conference on Neural Information Processing Systems

Code for reproducing Flow ++ experiments

Pytorch implementation of stochastically quantized variational autoencoder (SQ-VAE)

Pytorch implementation of Block Neural Autoregressive Flow