Alternatives and similar repositories for general-iv-models:

Users that are interested in general-iv-models are comparing it to the libraries listed below

• anndvision / quince
  Code for Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding
  ☆21Updated 2 years ago
• tansey / hrt
  The holdout randomization test: feature selection using black box predictive models
  ☆22Updated 3 years ago
• OATML / ucate
  Uncertainty in Conditional Average Treatment Effect Estimation
  ☆29Updated 3 years ago
• djsutherland / igms
  Implicit generative models and related stuff based on the MMD, in PyTorch
  ☆16Updated 4 years ago
• OATML / causal-bald
  ☆17Updated last year
• lopezpaz / causation_learning_theory
  Code for "Towards a learning theory of cause-effect inference" (ICML 2015).
  ☆29Updated 4 years ago
• aangelopoulos / private_prediction_sets
  Wrap around any model to output differentially private prediction sets with finite sample validity on any dataset.
  ☆17Updated 11 months ago
• rgiordan / CovariancesRobustnessVBPaper
  ☆11Updated last year
• blayes / WASP
  Scalable Bayes via Barycenter in Wasserstein Space
  ☆9Updated 7 years ago
• oxcsml / ML_bazaar
  OxCSML research group reading groups and meetings at the Department of Statistics, University of Oxford.
  ☆93Updated 3 years ago
• wittawatj / kernel-gof
  NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.
  ☆67Updated 5 years ago
• franrruiz / uivi
  Code for Unbiased Implicit Variational Inference (UIVI)
  ☆13Updated 6 years ago
• ermongroup / BiasAndGeneralization
  ☆26Updated 5 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆83Updated 3 years ago
• csinva / disentangled-attribution-curves
  Using / reproducing DAC from the paper "Disentangled Attribution Curves for Interpreting Random Forests and Boosted Trees"
  ☆27Updated 4 years ago
• pyro-ppl / sandbox
  Pyro models and misc examples.
  ☆19Updated 3 years ago
• jgorham / stein_discrepancy
  Code to compute the Stein discrepancy between a sample distribution and its target
  ☆16Updated 7 years ago
• yuachen / CausalDA
  Code to reproduce the numerical experiments in the paper Domain adaptation under structural causal models by Yuansi Chen and Peter Bühlma…
  ☆18Updated 3 years ago
• oval-group / ali-g
  Implementation of the ALI-G algorithm (PyTorch, Tensorflow)
  ☆22Updated 3 years ago
• cicl-stanford / csm
  Contains all materials for the paper "A counterfactual simulation model of causal judgment".
  ☆23Updated 3 years ago
• mrojascarulla / causal_transfer_learning
  ☆32Updated 6 years ago
• fated / libcp
  LibCP -- A Library for Conformal Prediction
  ☆11Updated 9 years ago
• adamhaber / stan2tfp
  stan2tfp is a lightweight interface to the TensorFlow Probability backend of the Stan compiler. It provides the necessary objects and fun…
  ☆24Updated 3 years ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆81Updated 8 months ago
• JonathanWenger / pycalib
  Non-Parametric Calibration for Classification (AISTATS 2020)
  ☆19Updated 3 years ago
• dmilios / dirichletGPC
  ☆17Updated 6 years ago
• aangelopoulos / rcps
  Official codebase for "Distribution-Free, Risk-Controlling Prediction Sets"
  ☆87Updated last year
• karalets / TyXe
  Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)
  ☆42Updated 3 years ago
• jan-glx / ICPy
  This packages provides a simple python implementation of Invariant Causal Prediction (ICP)
  ☆13Updated 10 months ago
• VivienCabannes / partial_labelling
  Learning with Partial Supervision
  ☆10Updated last year