google-research / disentanglement_libLinks
disentanglement_lib is an open-source library for research on learning disentangled representations.
☆1,415Updated 4 years ago
Alternatives and similar repositories for disentanglement_lib
Users that are interested in disentanglement_lib are comparing it to the libraries listed below
Sorting:
- Experiments for understanding disentanglement in VAE latent representations☆839Updated 2 years ago
- A curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.☆839Updated 4 years ago
- Pytorch implementation of β-VAE☆558Updated 5 years ago
- A curated list of research papers related to learning disentangled representations☆465Updated 6 years ago
- This repository contains notebook implementations of the following Neural Process variants: Conditional Neural Processes (CNPs), Neural P…☆1,010Updated 4 years ago
- Deep InfoMax (DIM), or "Learning Deep Representations by Mutual Information Estimation and Maximization"☆808Updated 6 years ago
- Implementations of various VAE-based semi-supervised and generative models in PyTorch☆710Updated 5 years ago
- Dataset to assess the disentanglement properties of unsupervised learning methods☆521Updated 5 years ago
- PyTorch implementations of algorithms for density estimation☆585Updated 4 years ago
- code for "Isolating Sources of Disentanglement in Variational Autoencoders".☆351Updated 3 years ago
- Pytorch implementation of JointVAE, a framework for disentangling continuous and discrete factors of variation☆470Updated 6 years ago
- higher is a pytorch library allowing users to obtain higher order gradients over losses spanning training loops rather than individual tr…☆1,627Updated 3 years ago
- Keras implementation of Representation Learning with Contrastive Predictive Coding☆549Updated 6 years ago
- Variational autoencoder implemented in tensorflow and pytorch (including inverse autoregressive flow)☆1,182Updated last year
- The Official PyTorch Implementation of "NVAE: A Deep Hierarchical Variational Autoencoder" (NeurIPS 2020 spotlight paper)☆1,084Updated 3 years ago
- Normalizing flows in PyTorch. Current intended use is education not production.☆906Updated 5 years ago
- Probabilistic Torch is library for deep generative models that extends PyTorch☆894Updated last year
- Wasserstein Auto-Encoders☆507Updated 7 years ago
- Disentanglement library for PyTorch☆283Updated 3 years ago
- Minimalist implementation of VQ-VAE in Pytorch☆556Updated 4 years ago
- code for "FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models".☆663Updated 5 years ago
- Project site for "Your Classifier is Secretly an Energy-Based Model and You Should Treat it Like One"☆426Updated 3 years ago
- [NeurIPS'19] Deep Equilibrium Models☆785Updated 3 years ago
- Pytorch implementations of density estimation algorithms: BNAF, Glow, MAF, RealNVP, planar flows☆637Updated 4 years ago
- ☆641Updated 4 years ago
- Vector Quantized VAEs - PyTorch Implementation☆945Updated 2 years ago
- Pytorch implementation of Hyperspherical Variational Auto-Encoders☆380Updated 5 years ago
- Code for the paper: Putting An End to End-to-End: Gradient-Isolated Learning of Representations☆291Updated 2 years ago
- Annotated, understandable, and visually interpretable PyTorch implementations of: VAE, BIRVAE, NSGAN, MMGAN, WGAN, WGANGP, LSGAN, DRAGAN,…☆505Updated 7 years ago
- Open source release of the evaluation benchmark suite described in "Realistic Evaluation of Deep Semi-Supervised Learning Algorithms"☆460Updated 6 years ago