google-research / disentanglement_lib
disentanglement_lib is an open-source library for research on learning disentangled representations.
☆1,392Updated 3 years ago
Alternatives and similar repositories for disentanglement_lib:
Users that are interested in disentanglement_lib are comparing it to the libraries listed below
- Experiments for understanding disentanglement in VAE latent representations☆803Updated last year
- Dataset to assess the disentanglement properties of unsupervised learning methods☆489Updated 4 years ago
- A curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.☆793Updated 3 years ago
- A curated list of research papers related to learning disentangled representations☆463Updated 5 years ago
- Implementations of various VAE-based semi-supervised and generative models in PyTorch☆707Updated 4 years ago
- PyTorch implementations of algorithms for density estimation☆577Updated 3 years ago
- Pytorch implementation of β-VAE☆532Updated 4 years ago
- Pytorch implementation of JointVAE, a framework for disentangling continuous and discrete factors of variation☆463Updated 5 years ago
- Deep InfoMax (DIM), or "Learning Deep Representations by Mutual Information Estimation and Maximization"☆807Updated 5 years ago
- Disentanglement library for PyTorch☆277Updated 2 years ago
- code for "Isolating Sources of Disentanglement in Variational Autoencoders".☆346Updated 2 years ago
- Normalizing flows in PyTorch. Current intended use is education not production.☆850Updated 4 years ago
- higher is a pytorch library allowing users to obtain higher order gradients over losses spanning training loops rather than individual tr…☆1,601Updated 2 years ago
- The Official PyTorch Implementation of "NVAE: A Deep Hierarchical Variational Autoencoder" (NeurIPS 2020 spotlight paper)☆1,038Updated 2 years ago
- Probabilistic Torch is library for deep generative models that extends PyTorch☆887Updated 8 months ago
- Wasserstein Auto-Encoders☆507Updated 6 years ago
- Project site for "Your Classifier is Secretly an Energy-Based Model and You Should Treat it Like One"☆418Updated 2 years ago
- code for "FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models".☆634Updated 4 years ago
- Official Code for Invertible Residual Networks☆522Updated 5 months ago
- Pytorch implementations of density estimation algorithms: BNAF, Glow, MAF, RealNVP, planar flows☆609Updated 3 years ago
- Variational autoencoder implemented in tensorflow and pytorch (including inverse autoregressive flow)☆1,160Updated 8 months ago
- MADE (Masked Autoencoder Density Estimation) implementation in PyTorch☆544Updated 6 years ago
- Pytorch implementation of FactorVAE proposed in Disentangling by Factorising(http://arxiv.org/abs/1802.05983)☆265Updated 6 years ago
- Pytorch implementation of Hyperspherical Variational Auto-Encoders☆357Updated 4 years ago
- A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch☆2,004Updated last year
- Open source release of the evaluation benchmark suite described in "Realistic Evaluation of Deep Semi-Supervised Learning Algorithms"☆460Updated 5 years ago
- Minimalist implementation of VQ-VAE in Pytorch☆528Updated 3 years ago
- Code for the paper: Putting An End to End-to-End: Gradient-Isolated Learning of Representations☆285Updated last year
- Repository for the paper "Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images"☆433Updated last year
- Toolbox to integrate optimal transport loss functions using automatic differentiation and Sinkhorn's algorithm☆437Updated 6 years ago