Henrilin28 / awesome-Interpretable-MLLinks
A curated list for interpretable machine learning
☆18Updated 6 years ago
Alternatives and similar repositories for awesome-Interpretable-ML
Users that are interested in awesome-Interpretable-ML are comparing it to the libraries listed below
Sorting:
- Dynamic causal Bayesian optimisation☆40Updated 2 years ago
- Seminar on Limitations of Interpretable Machine Learning Methods☆57Updated 5 years ago
- An AutoML pipeline selection system to quickly select a promising pipeline for a new dataset.☆82Updated 4 years ago
- Data and code related to the paper "Probabilistic matrix factorization for automated machine learning", NIPS, 2018.☆40Updated 4 years ago
- Code for the WSDM '20 paper, Learning Individual Causal Effects from Networked Observational Data.☆77Updated 4 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
- Reading list for "The Shapley Value in Machine Learning" (JCAI 2022)☆153Updated 3 years ago
- ☆30Updated last year
- Official code repository to the corresponding paper.☆29Updated 2 years ago
- Code and data for decision making under strategic behavior, NeurIPS 2020 & Management Science 2024.☆29Updated last year
- ☆12Updated 2 years ago
- stand alone Neural Additive Models, forked from google-reasearch for easy import to colab☆29Updated 5 years ago
- (ICML2020) “Counterfactual Cross-Validation: Stable Model Selection Procedure for Causal Inference Models’’☆31Updated 2 years ago
- Generalized additive model with pairwise interactions☆67Updated last year
- Awesome papers on Feature Selection☆36Updated last year
- Python implementation of the Iterative Classification Algorithm☆35Updated 8 years ago
- Time series forecasting with PyTorch☆86Updated 2 weeks ago
- An open-source package of causal feature selection and causal (Bayesian network) structure learning (C/C++ version)☆64Updated 5 years ago
- ☆25Updated 4 years ago
- For calculating Shapley values via linear regression.☆71Updated 4 years ago
- Code for ICML 2020 paper: "Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders" by I. …☆52Updated 4 years ago
- A collection of algorithms of counterfactual explanations.☆52Updated 4 years ago
- Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)☆54Updated 4 years ago
- Python library for working with graphons☆23Updated 8 years ago
- Data derived from the Linked Births and Deaths Data (LBIDD); simulated pairs of treatment assignment and outcomes; scoring code☆84Updated 7 years ago
- Kaggle's Causality Challenge Solution for team FirfiD☆26Updated 12 years ago
- A curated list of graph learning papers, articles, tutorials, slides and projects☆30Updated 5 years ago
- A Causal Decision Tree algorithm for causality inference with continuous variables☆22Updated 4 years ago
- Python code for NeurIPS 2018 paper "Causal Inference and Mechanism Clustering of A Mixture of Additive Noise Models"☆23Updated 6 years ago
- Causing: CAUsal INterpretation using Graphs☆60Updated this week