Alternatives and similar repositories for causation_learning_theory

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

• wittawatj / interpretable-test
  NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.
  ☆63Updated 7 years ago
• rgiordan / CovariancesRobustnessVBPaper
  ☆11Updated last year
• wittawatj / kernel-gof
  NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.
  ☆67Updated 5 years ago
• franrruiz / p-emb
  Exponential family embeddings (Poisson or Bernoulli) for discrete data
  ☆32Updated 5 years ago
• dadaromeo / recsys-hpf
  Movies Recommendation with Hierarchical Poisson Factorization in Edward
  ☆18Updated 7 years ago
• mrkulk / SequentialInference
  Dirichlet Process Mixture using PVI, SMC, Variational
  ☆15Updated 10 years ago
• BigBayes / SGRLD
  Stochastic Gradient Riemannian Langevin Dynamics
  ☆33Updated 10 years ago
• ivaleraM / GLFM
  General Latent Feature Modeling for Heterogeneous data
  ☆49Updated last year
• tansey / hrt
  The holdout randomization test: feature selection using black box predictive models
  ☆21Updated 4 years ago
• mkocaoglu / Entropic-Causality
  ☆10Updated 8 years ago
• nikikilbertus / general-iv-models
  Bounding causal effects in general (continuous, non-additive) instrumental variable models.
  ☆14Updated last year
• mauriziofilippone / deep_gp_random_features
  ☆40Updated 6 years ago
• blei-lab / zero-inflated-embedding
  Code for the icml paper "zero inflated exponential family embedding"
  ☆29Updated 7 years ago
• wangtongada / BOA
  Bayesian or-of-and
  ☆34Updated 3 years ago
• STOR-i / sgmcmc
  sgmcmc: a stochastic gradient MCMC package for R
  ☆29Updated 4 years ago
• christinaheinze / nonlinearICP-and-CondIndTests
  Code for a variety of nonlinear conditional independence tests and 'nonlinear Invariant Causal Prediction' to estimate the causal parents…
  ☆17Updated 5 years ago
• oxcsml / kerpy
  python code for kernel methods
  ☆38Updated 6 years ago
• alshedivat / DeterminantalPointProcesses.jl
  Determinantal Point Processes in Julia
  ☆12Updated 5 years ago
• diviyank / SAM
  Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)
  ☆52Updated 4 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆85Updated 3 years ago
• mkocaoglu / CausalGAN
  ☆142Updated 7 years ago
• rjagerman / wsdm2019-nonstationary
  Non-stationary Off-policy Evaluation
  ☆13Updated 6 years ago
• cicl-stanford / csm
  Contains all materials for the paper "A counterfactual simulation model of causal judgment".
  ☆24Updated 3 years ago
• lightlightdyy / Deep-Learning-and-Causal-Inference
  ☆29Updated 6 years ago
• andymiller / ReducedVarianceReparamGradients
  Reducing Reparameterization Gradient Variance code.
  ☆33Updated 8 years ago
• mrojascarulla / causal_transfer_learning
  ☆32Updated 6 years ago
• duvenaud / deep-limits
  Repo for a paper about constructing priors on very deep models.
  ☆73Updated 8 years ago
• zixu1986 / Doubly_Stochastic_Gradients
  Code for doubly stochastic gradients
  ☆25Updated 10 years ago
• didriknielsen / ds3_abi_exercises
  Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018
  ☆22Updated 6 years ago
• chrisdxie / in-depth-VI-tutorial
  ☆11Updated 8 years ago