CausalML / interventions-disparate-impact-respondersLinks
Assessing Disparate Impacts of Personalized Interventions: Identifiability and Bounds
☆11Updated 6 years ago
Alternatives and similar repositories for interventions-disparate-impact-responders
Users that are interested in interventions-disparate-impact-responders are comparing it to the libraries listed below
Sorting:
- An Interface to Specify Causal Graphs and Compute Balke Bounds☆22Updated 10 months ago
- 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
- Demo data and code for "Sense and Sensitivity Analysis: Simple Post-Hoc Analysis of Bias Due to Unobserved Confounding".☆27Updated 4 years ago
- ☆12Updated 6 years ago
- The holdout randomization test: feature selection using black box predictive models☆22Updated 4 years ago
- CausalFX R Package☆13Updated 10 years ago
- Non-parametrics for Causal Inference☆50Updated 3 years ago
- Perform bayesian distribution regression☆13Updated 7 years ago
- General Latent Feature Modeling for Heterogeneous data☆50Updated last year
- Code for "Towards a learning theory of cause-effect inference" (ICML 2015).☆30Updated 5 years ago
- TensorFlow implementation of 'Core', proposed in "Conditional Variance Penalties and Domain Shift Robustness".☆10Updated 7 years ago
- Code to run submissions for the Atlantic Causal Inference Competition☆44Updated last year
- An optimization-based algorithm to accurately estimate the causal effects and robustly predict under distribution shifts. It leverages th…☆14Updated last year
- Data for and description of the ACIC 2023 data competition☆32Updated 2 years ago
- Approximately balanced estimation of average treatment effects in high dimensions.☆35Updated 4 years ago
- Code and data for the experiments in "On Fairness and Calibration"☆51Updated 3 years ago
- Implementation of Deep IV: A Flexible Approach for Counterfactual Prediction☆161Updated 4 years ago
- Tutorial in randomization inference, experimental design and analysis, and experiments in networks.☆30Updated 9 years ago
- Implementation of algorithms from the paper "Globally-Consistent Rule-Based Summary-Explanations for Machine Learning Models: Application…☆25Updated 3 years ago
- Bayesian or-of-and☆36Updated 3 years ago
- ☆11Updated 7 years ago
- Unbiased Markov chain Monte Carlo with couplings☆30Updated 3 years ago
- Data and code related to the paper "Probabilistic matrix factorization for automated machine learning", NIPS, 2018.☆40Updated 4 years ago
- Implements the model described in "Identification, Interpretability, and Bayesian Word Embeddings"☆19Updated 6 years ago
- (ICML2020) “Counterfactual Cross-Validation: Stable Model Selection Procedure for Causal Inference Models’’☆31Updated 2 years ago
- The pygformula implements the parametric g-formula in Python. The parametric g-formula (Robins, 1986) uses longitudinal data with time-va…☆30Updated last month
- R code for ''Bayesian method for causal inference in spatially-correlated multivariate time series''☆45Updated 5 years ago
- Seminar on Limitations of Interpretable Machine Learning Methods☆57Updated 5 years ago
- ☆44Updated 4 years ago
- Software and pre-processed data for "Using Embeddings to Correct for Unobserved Confounding in Networks"☆57Updated 2 years ago