Alternatives and similar repositories for CausalGAN:

Users that are interested in CausalGAN are comparing it to the libraries listed below

• djsutherland / opt-mmd
  Learning kernels to maximize the power of MMD tests
  ☆210Updated 7 years ago
• diviyank / SAM
  Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)
  ☆52Updated 4 years ago
• casperkaae / LVAE
  Code for "How to Train Deep Variational Autoencoders and Probabilistic Ladder Networks"
  ☆101Updated 9 years ago
• wittawatj / interpretable-test
  NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.
  ☆63Updated 6 years ago
• fengliu90 / DK-for-TST
  This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).
  ☆49Updated 3 years ago
• GoudetOlivier / CGNN
  Replication code for the article "Learning Functional Causal Models with Generative Neural Networks"
  ☆99Updated 5 years ago
• ermongroup / Sequential-Variational-Autoencoder
  Implementation of Sequential Variational Autoencoder
  ☆88Updated 7 years ago
• nke001 / causal_learning_unknown_interventions
  Code for "Neural causal learning from unknown interventions"
  ☆101Updated 4 years ago
• maxwshen / iap-cidl
  Causal Inference & Deep Learning, MIT IAP 2018
  ☆88Updated 7 years ago
• steveli / misgan
  MisGAN: Learning from Incomplete Data with GANs
  ☆81Updated last year
• microsoft / deterministic-variational-inference
  Sample code for running deterministic variational inference to train Bayesian neural networks
  ☆100Updated 6 years ago
• MichaelArbel / Scaled-MMD-GAN
  Scaled MMD GAN
  ☆36Updated 5 years ago
• oxcsml / kerpy
  python code for kernel methods
  ☆38Updated 6 years ago
• blei-lab / ars-reparameterization
  Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)
  ☆39Updated 8 years ago
• dongyp13 / Robust-and-Explainable-Machine-Learning
  Related materials for robust and explainable machine learning
  ☆48Updated 7 years ago
• LMescheder / AdversarialVariationalBayes
  This repository contains the code to reproduce the core results from the paper "Adversarial Variational Bayes: Unifying Variational Autoe…
  ☆206Updated 7 years ago
• iffsid / disentangling-disentanglement
  ☆91Updated 5 years ago
• yujiali / gmmn
  Generative moment matching networks
  ☆149Updated 8 years ago
• dcmoyer / inv-rep
  Code for Invariant Rep. Without Adversaries (NIPS 2018)
  ☆35Updated 5 years ago
• mrojascarulla / causal_transfer_learning
  ☆32Updated 6 years ago
• ctallec / pyvarinf
  Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch
  ☆359Updated 5 years ago
• facebookresearch / InvarianceUnitTests
  Toy datasets to evaluate algorithms for domain generalization and invariance learning.
  ☆42Updated 3 years ago
• lopezpaz / causation_learning_theory
  Code for "Towards a learning theory of cause-effect inference" (ICML 2015).
  ☆29Updated 4 years ago
• fpcasale / GPPVAE
  Gaussian Process Prior Variational Autoencoder
  ☆83Updated 6 years ago
• kevin-w-li / deep-kexpfam
  ☆28Updated 3 years ago
• daib13 / TwoStageVAE
  ☆237Updated 5 years ago
• marcofraccaro / srnn
  Code for "Sequential Neural Models with Stochastic Layers"
  ☆117Updated 8 years ago
• brain-research / ncp
  Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors
  ☆62Updated 5 years ago
• YingzhenLi / vae_renyi_divergence
  A tensorflow implementation of VAE training with Renyi divergence
  ☆31Updated 8 years ago
• RuiShu / vae-experiments
  Code for some of the experiments I did with variational autoencoders on multi-modality and atari video prediction. Atari video prediction…
  ☆62Updated 8 years ago