fredthedead / causal-inference-in-statistics-solutionsLinks
Solutions on "Causal Inference in Statistics: A Primer" using Jupyter Notebook, Python
☆31Updated 7 years ago
Alternatives and similar repositories for causal-inference-in-statistics-solutions
Users that are interested in causal-inference-in-statistics-solutions are comparing it to the libraries listed below
Sorting:
- Notes for Judea Pearl et al., *Causal Inference in Statistics, a Primer*☆68Updated 6 years ago
- A curated list of awesome work on causal inference, particularly in machine learning.☆112Updated 4 years ago
- A (concise) curated list of awesome Causal Inference resources.☆255Updated 3 years ago
- References for Papers at the Intersection of Causality and Fairness☆18Updated 7 years ago
- Resources related to causality☆267Updated last year
- Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.☆32Updated 6 years ago
- Causal Effect Inference for Structured Treatments (SIN) (NeurIPS 2021)☆42Updated 3 years ago
- Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831☆37Updated 3 years ago
- Code for ICLR 2020 paper: "Estimating counterfactual treatment outcomes over time through adversarially balanced representations" by I. B…☆67Updated last year
- Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…☆86Updated 4 years ago
- ☆33Updated 7 years ago
- Code for "Neural causal learning from unknown interventions"☆104Updated 5 years ago
- Code and results accompanying our paper titled Mixture Proportion Estimation and PU Learning: A Modern Approach at Neurips 2021 (Spotligh…☆46Updated last year
- ☆30Updated 7 years ago
- Code for "Generative causal explanations of black-box classifiers"☆35Updated 5 years ago
- Implementation of Deep IV: A Flexible Approach for Counterfactual Prediction☆161Updated 4 years ago
- Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.☆132Updated 5 years ago
- A data index for learning causality.☆482Updated 2 years ago
- ☆30Updated 3 years ago
- ☆65Updated last year
- Neural Additive Models (Google Research)☆74Updated 4 years ago
- Causal Inference & Deep Learning, MIT IAP 2018☆89Updated 8 years ago
- Flowchart to help choose which causal inference book to read. See https://bradyneal.github.io/which-causal-inference-book for more info s…☆60Updated 6 years ago
- ☆32Updated 4 years ago
- Code for the NIPS 2018 paper "Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions"☆18Updated 4 years ago
- 💉📈 Dose response networks (DRNets) are a method for learning to estimate individual dose-response curves for multiple parametric treatm…☆93Updated 2 years ago
- 把因果思维融入机器学习中☆81Updated 6 years ago
- ☆45Updated 3 years ago
- Code for our ICML '19 oral paper: Neural Network Attributions: A Causal Perspective.☆51Updated 4 years ago
- Software and pre-processed data for "Using Embeddings to Correct for Unobserved Confounding in Networks"☆57Updated 2 years ago