Alternatives and similar repositories for dgcit

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

• jjcherian / fairaudit
  Statistical inference for fairness auditing
  ☆14Updated 2 years ago
• alexisbellot / GCIT
  Conditional Independence Testing with Generative Adversarial Networks
  ☆14Updated 6 years ago
• christinaheinze / core
  TensorFlow implementation of 'Core', proposed in "Conditional Variance Penalties and Domain Shift Robustness".
  ☆10Updated 7 years ago
• kjchalup / independence_test
  A deep-learning-based conditional independence test that works for big, high-dimensional data.
  ☆14Updated 8 years ago
• uhlerlab / actlearn_optint
  Active learning for optimal intervention design in causal models
  ☆16Updated 2 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 4 years ago
• uhlerlab / causaldag
  Python package for the creation, manipulation, and learning of Causal DAGs
  ☆155Updated 2 years ago
• msesia / deepknockoffs
  Approximate knockoffs and model-free variable selection.
  ☆56Updated 4 years ago
• anishazaveri / austen_plots
  Demo data and code for "Sense and Sensitivity Analysis: Simple Post-Hoc Analysis of Bias Due to Unobserved Confounding".
  ☆26Updated 4 years ago
• rajatsen91 / CCIT
  Classifier Conditional Independence Test: A CI test that uses a binary classifier (XGBoost) for CI testing
  ☆47Updated 2 years ago
• christinaheinze / CompareCausalNetworks
  A unified interface for the estimation of causal networks
  ☆22Updated 5 years ago
• bradyneal / realcause
  Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…
  ☆84Updated 4 years ago
• caus-am / jci
  Code for the paper "Joint Causal Inference from Multiple Contexts" (JMLR 2020)
  ☆16Updated 5 years ago
• nikikilbertus / cf-fairness-sensitivity
  The code for the paper *The Sensitivity of Counterfactual Fairness to Unmeasured Confounding* @ UAI 2019
  ☆14Updated 5 years ago
• ilkhem / iVAE
  VAEs and nonlinear ICA: a unifying framework
  ☆39Updated 5 years ago
• edfong / conformal_bayes
  Conformal Bayes with importance sampling
  ☆23Updated 4 years ago
• aangelopoulos / private_prediction_sets
  Wrap around any model to output differentially private prediction sets with finite sample validity on any dataset.
  ☆18Updated last year
• statmlben / dnn-inference
  Significance tests of feature relevance for a black-box learner
  ☆19Updated last year
• larslorch / avici
  Amortized Inference for Causal Structure Learning, NeurIPS 2022
  ☆68Updated 10 months ago
• bdwilliamson / vimpy
  Perform inference on algorithm-agnostic variable importance in Python
  ☆21Updated 3 years ago
• slachapelle / dcdi
  Repository for "Differentiable Causal Discovery from Interventional Data"
  ☆77Updated 3 years ago
• soda-inria / caussim
  Simulations for predictive model selection in causal inference
  ☆13Updated 10 months ago
• tijana-zrnic / active-inference
  ☆17Updated last year
• nikikilbertus / fairensics
  A python library to discover and mitigate biases in machine learning models and datasets
  ☆20Updated 2 years ago
• larslorch / stadion
  Causal Modeling with Stationary Diffusions, AISTATS 2024
  ☆20Updated 9 months ago
• vdorie / npci
  Non-parametrics for Causal Inference
  ☆50Updated 3 years ago
• chunlinli / defuse
  Nonlinear Causal Discovery with Confounders
  ☆21Updated 2 years ago
• fabian-sp / lassonet
  An implementation of LassoNet for arbitrary network architectures
  ☆14Updated 3 years ago
• xwshen51 / DistributionalPrincipalAutoencoder
  ☆12Updated last year
• larslorch / dibs
  DiBS: Differentiable Bayesian Structure Learning, NeurIPS 2021
  ☆51Updated last year