AlxndrMlk / blogs-codeLinks
Code for blog posts.
☆20Updated 2 years ago
Alternatives and similar repositories for blogs-code
Users that are interested in blogs-code are comparing it to the libraries listed below
Sorting:
- GRAPL: A computational library for nonparametric structural causal modelling, analysis and inference☆83Updated 10 months ago
- A Python Package providing two algorithms, DAME and FLAME, for fast and interpretable treatment-control matches of categorical data☆62Updated 3 months ago
- Machine Learning models using a Bayesian approach and often PyMC3☆25Updated 4 years ago
- causal-falsify: A Python library with algorithms for falsifying unconfoundedness assumption in a composite dataset from multiple sources.☆35Updated 2 months ago
- Surrogate Assisted Feature Extraction☆37Updated 4 years ago
- [ NeurIPS 2023 ] Official Codebase for "Conformal Meta-learners for Predictive Inference of Individual Treatment Effects"☆45Updated 2 years ago
- 💊 Comparing causality methods in a fair and just way.☆140Updated 5 years ago
- [Experimental] Causal graphs that are networkx-compliant for the py-why ecosystem.☆62Updated this week
- 🪜 Bayesian Hierarchical Models at Scale☆51Updated 4 years ago
- ☆14Updated last year
- A full example for causal inference on real-world retail data, for elasticity estimation☆52Updated 4 years ago
- Causal Inference in Python☆44Updated last month
- Unstructured Code with interesting analysis☆37Updated last year
- Implementation of algorithms from the paper "Globally-Consistent Rule-Based Summary-Explanations for Machine Learning Models: Application…☆25Updated 3 years ago
- A python package for hierarchical forecasting, inspired by hts package in R.☆29Updated 8 months ago
- An R package for computing asymmetric Shapley values to assess causality in any trained machine learning model☆74Updated 5 years ago
- Causing: CAUsal INterpretation using Graphs☆59Updated last week
- Interpretable, intuitive outlier detector intended for categorical and numeric data.☆12Updated last year
- An extension of CatBoost to probabilistic modelling☆148Updated 2 years ago
- XAI Stories. Case studies for eXplainable Artificial Intelligence☆31Updated 5 years ago
- The cause2e package provides tools for performing an end-to-end causal analysis of your data. Developed by Daniel Grünbaum (@dg46).☆63Updated 6 months ago
- Active Bayesian Causal Inference (Neurips'22)☆58Updated last year
- Python library to explain Tree Ensemble models (TE) like XGBoost, using a rule list.☆60Updated last year
- Causal Inference Using Quasi-Experimental Methods☆20Updated 4 years ago
- ☆24Updated last month
- Source code for the paper "Causal Modeling of Twitter Activity during COVID-19". Computation, 2020.☆10Updated 2 years ago
- This project introduces Causal AI and how it can drive business value.☆52Updated last year
- Bayesian time series forecasting and decision analysis☆119Updated 2 years ago
- EconML/CausalML KDD 2021 Tutorial☆163Updated 2 years ago
- python app for doing personalized causal medicine using the methods invented by Judea Pearl et al.☆25Updated 2 years ago