microsoft / reliableAILinks
☆46Updated last week
Alternatives and similar repositories for reliableAI
Users that are interested in reliableAI are comparing it to the libraries listed below
Sorting:
- Interpretable and efficient predictors using pre-trained language models. Scikit-learn compatible.☆42Updated 3 months ago
- Solving the causality pairs challenge (does A cause B) with ChatGPT☆77Updated last year
- A python package for modeling, persisting and visualizing causal graphs embedded in knowledge graphs.☆56Updated last year
- Causal Effect Inference for Structured Treatments (SIN) (NeurIPS 2021)☆42Updated 3 years ago
- Uses several statistical tests / algorithms on marginal / conditional distributions☆8Updated last year
- CSuite: A Suite of Benchmark Datasets for Causality☆67Updated 2 years ago
- The code of AAAI 2020 paper "Transparent Classification with Multilayer Logical Perceptrons and Random Binarization".☆24Updated last year
- Source code of AAAI'22 paper: A Hybrid Causal Structure Learning Algorithm for Mixed-type Data☆38Updated 3 years ago
- Influence Estimation for Gradient-Boosted Decision Trees☆27Updated last year
- [Experimental] Causal graphs that are networkx-compliant for the py-why ecosystem.☆56Updated this week
- Testing Language Models for Memorization of Tabular Datasets.☆33Updated 4 months ago
- [Experimental] Global causal discovery algorithms☆103Updated this week
- ☆66Updated 2 years ago
- The code of NeurIPS 2021 paper "Scalable Rule-Based Representation Learning for Interpretable Classification" and TPAMI paper "Learning I…☆112Updated last year
- ☆13Updated 6 months ago
- Implementations of methods proposed in the paper "Conformal Prediction Sets for Graph Neural Networks"☆14Updated 2 years ago
- Datasets for Causal-Structure-Learning Repo☆15Updated 5 years ago
- Example causal datasets with consistent formatting and ground truth☆84Updated 2 months ago
- ☆30Updated last year
- Foundation Models for Data Tasks☆106Updated 2 years ago
- For calculating Shapley values via linear regression.☆68Updated 4 years ago
- XAI-Bench is a library for benchmarking feature attribution explainability techniques☆68Updated 2 years ago
- Official implementation of the paper "Interventions, Where and How? Experimental Design for Causal Models at Scale", NeurIPS 2022.☆20Updated 2 years ago
- Salesforce CausalAI Library: A Fast and Scalable framework for Causal Analysis of Time Series and Tabular Data☆292Updated last month
- Reimplementation of NOTEARS in Tensorflow☆33Updated 2 years ago
- [SDM'23] ML4C: Seeing Causality Through Latent Vicinity☆12Updated 2 years ago
- Learning clinical-decision rules with interpretable models.☆20Updated last year
- Official implementation of Optimized Feature Generation for Tabular Data via LLMs with Decision Tree Reasoning (NeurIPS 2024).☆17Updated 3 months ago
- Code accompanying the paper "Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers"☆31Updated 2 years ago
- Rule Extraction Methods for Interactive eXplainability☆43Updated 3 years ago