Awesome resources on normalizing flows.
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Updated
Sep 24, 2024 - Python
Awesome resources on normalizing flows.
Normalizing flows in PyTorch
PyTorch implementation of normalizing flow models
PyTorch implementations of algorithms for density estimation
Reimplementation of Variational Inference with Normalizing Flows (https://arxiv.org/abs/1505.05770)
Implementation of normalizing flows in TensorFlow 2 including a small tutorial.
Pytorch implementation of Block Neural Autoregressive Flow
Neural Relation Understanding: neural cardinality estimators for tabular data
Libraries to analyze numerical simulations (python3)
Density estimation likelihood-free inference. No longer actively developed see https://github.com/mackelab/sbi instead
Code for reproducing Flow ++ experiments
Real NVP PyTorch a Minimal Working Example | Normalizing Flow
Manifold-learning flows (ℳ-flows)
[CVPR 2021 Oral] Official PyTorch implementation of Soft-IntroVAE from the paper "Soft-IntroVAE: Analyzing and Improving Introspective Variational Autoencoders"
Estimators for the entropy and other information theoretic quantities of continuous distributions
Normalizing flows in PyTorch
Density estimation using Gaussian mixtures in the presence of noisy, heterogeneous and incomplete data
Code for reproducing results in the sliced score matching paper (UAI 2019)
Probabilistic Learning for mlr3
Distance-based Analysis of DAta-manifolds in python
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