karpathy / pytorch-normalizing-flowsLinks
Normalizing flows in PyTorch. Current intended use is education not production.
☆881Updated 5 years ago
Alternatives and similar repositories for pytorch-normalizing-flows
Users that are interested in pytorch-normalizing-flows are comparing it to the libraries listed below
Sorting:
- PyTorch implementations of algorithms for density estimation☆585Updated 4 years ago
- Pytorch implementations of density estimation algorithms: BNAF, Glow, MAF, RealNVP, planar flows☆633Updated 4 years ago
- code for "FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models".☆657Updated 5 years ago
- MADE (Masked Autoencoder Density Estimation) implementation in PyTorch☆566Updated 6 years ago
- [NeurIPS'19] Deep Equilibrium Models☆767Updated 3 years ago
- Simple, extendable, easy to understand Glow implementation in PyTorch☆386Updated 3 years ago
- Normalizing flows in PyTorch☆959Updated 9 months ago
- ☆818Updated 5 months ago
- Neural Spline Flow, RealNVP, Autoregressive Flow, 1x1Conv in PyTorch.☆280Updated last year
- Tutorial on normalizing flows.☆299Updated 7 years ago
- Code for paper "SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows"☆288Updated 4 years ago
- Official Code for Invertible Residual Networks☆531Updated last year
- Implementation of Real NVP in PyTorch☆237Updated 6 years ago
- Code for Neural Spline Flows paper☆279Updated 5 years ago
- This repository contains notebook implementations of the following Neural Process variants: Conditional Neural Processes (CNPs), Neural P…☆1,003Updated 4 years ago
- Course notes☆721Updated last year
- Dataset to assess the disentanglement properties of unsupervised learning methods☆515Updated 4 years ago
- Experiments for understanding disentanglement in VAE latent representations☆828Updated 2 years ago
- Probabilistic Torch is library for deep generative models that extends PyTorch☆891Updated last year
- code for "Residual Flows for Invertible Generative Modeling".☆272Updated 2 years ago
- disentanglement_lib is an open-source library for research on learning disentangled representations.☆1,407Updated 4 years ago
- A curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.☆825Updated 4 years ago
- Pytorch implementation of JointVAE, a framework for disentangling continuous and discrete factors of variation☆468Updated 6 years ago
- Pytorch implementation of Augmented Neural ODEs☆552Updated 2 years ago
- BackPACK - a backpropagation package built on top of PyTorch which efficiently computes quantities other than the gradient.☆590Updated 9 months ago
- Totally Versatile Miscellanea for Pytorch☆475Updated 3 years ago
- Reimplementation of Variational Inference with Normalizing Flows (https://arxiv.org/abs/1505.05770)☆235Updated 7 years ago
- Constrained optimization toolkit for PyTorch☆698Updated 2 months ago
- VQVAEs, GumbelSoftmaxes and friends☆587Updated 3 years ago
- Pytorch implementation of Hyperspherical Variational Auto-Encoders☆374Updated 5 years ago