BeanHam / 2019-interpretable-machine-learning
☆10Updated 2 years ago
Related projects ⓘ
Alternatives and complementary repositories for 2019-interpretable-machine-learning
- TIme series DiscoverY BENCHmark (tidybench)☆37Updated 8 months ago
- Causal Discovery with Equal Variance Assumption☆9Updated 2 years ago
- A Python Package providing two algorithms, DAME and FLAME, for fast and interpretable treatment-control matches of categorical data☆57Updated 5 months ago
- Software and pre-processed data for "Using Embeddings to Correct for Unobserved Confounding in Networks"☆55Updated last year
- A curated list of awesome work on causal inference, particularly in machine learning.☆96Updated 3 years ago
- Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…☆68Updated 3 years ago
- ☆37Updated 5 years ago
- GRAPL: A computational library for nonparametric structural causal modelling, analysis and inference☆78Updated 11 months ago
- Conditional calibration of conformal p-values for outlier detection.☆33Updated last year
- A set of kernel-based (Un)conditional independence tests including SDCIT (Lee and Honavar, UAI 2017)☆15Updated 4 years ago
- Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)☆53Updated 3 years ago
- Project on Causal Machine learning CS 7290☆16Updated 4 years ago
- Code and data for decision making under strategic behavior, NeurIPS 2020 & Management Science 2024.☆27Updated 8 months ago
- Training quantile models☆39Updated 3 years ago
- ☆29Updated 5 years ago
- Demo data and code for "Sense and Sensitivity Analysis: Simple Post-Hoc Analysis of Bias Due to Unobserved Confounding".☆25Updated 2 years ago
- This repository captures source code and data sets for our paper at the Causal Discovery & Causality-Inspired Machine Learning Workshop a…☆59Updated 2 months ago
- CSuite: A Suite of Benchmark Datasets for Causality☆58Updated last year
- Code for ICML 2020 paper: "Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders" by I. …☆51Updated 3 years ago
- Non-parametrics for Causal Inference☆43Updated 2 years ago
- Tensorflow 2 implementation of Causal-BERT☆69Updated last year
- Solving the causality pairs challenge (does A cause B) with ChatGPT☆75Updated 5 months ago
- LEAP is a tool for discovering latent temporal causal relations with gradient-based neural network.☆34Updated 2 years ago
- ☆10Updated 5 years ago
- Code to reproduce the numerical experiments in the paper Domain adaptation under structural causal models by Yuansi Chen and Peter Bühlma…☆18Updated 3 years ago
- Reimplementation of NOTEARS in Tensorflow☆32Updated last year
- Example causal datasets with consistent formatting and ground truth☆66Updated last year
- Code for Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding☆21Updated last year
- Neural Additive Models (Google Research)☆67Updated 3 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…☆58Updated 4 years ago