jpmorganchase / cf-shap
Counterfactual SHAP: a framework for counterfactual feature importance
☆16Updated last year
Related projects: ⓘ
- A lightweight implementation of removal-based explanations for ML models.☆56Updated 3 years ago
- Testing Language Models for Memorization of Tabular Datasets.☆26Updated last week
- Extending Conformal Prediction to LLMs☆53Updated 3 months ago
- Mothernet: A Foundational Hypernetwork for Tabular Classification☆26Updated this week
- Causal Inference in Python☆36Updated last month
- Code and data for decision making under strategic behavior, NeurIPS 2020 & Management Science 2024.☆26Updated 6 months ago
- Multi-class probabilistic classification using inductive and cross Venn–Abers predictors☆43Updated 2 years ago
- ☆14Updated 4 months ago
- Code for Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding☆21Updated last year
- A Natural Language Interface to Explainable Boosting Machines☆59Updated 2 months ago
- All the material needed to use MC-CP and the Adaptive MC Dropout method☆21Updated last month
- Adaptive and Reliable Classification: efficient conformity scores for multi-class classification problems☆31Updated last year
- Experimental library integrating LLM capabilities to support causal analyses☆70Updated last week
- stand alone Neural Additive Models, forked from google-reasearch for easy import to colab☆26Updated 3 years ago
- Official code repository to the corresponding paper.☆28Updated last year
- GAMI-Net: Generalized Additive Models with Structured Interactions☆30Updated 2 years ago
- Rule Extraction Methods for Interactive eXplainability☆40Updated 2 years ago
- Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)☆38Updated last year
- A Causal AI package for causal graphs.☆50Updated this week
- Dynamic causal Bayesian optimisation☆32Updated last year
- ☆16Updated 3 years ago
- CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox☆42Updated last month
- The Medkit-Learn(ing) Environment: Medical Decision Modelling through Simulation (NeurIPS 2021) by Alex J. Chan, Ioana Bica, Alihan Huyuk…☆27Updated 2 years ago
- Python package to compute interaction indices that extend the Shapley Value. AISTATS 2023.☆17Updated 11 months ago
- A collection of algorithms of counterfactual explanations.☆47Updated 3 years ago
- Learning clinical-decision rules with interpretable models.☆18Updated last year
- Fast implementation of Venn-ABERS probabilistic predictors☆69Updated 7 months ago
- Official repository for the ICML 2022 DFUQ paper: conformal prediction sets for time-series☆10Updated 2 years ago
- Uncertainty in Conditional Average Treatment Effect Estimation☆26Updated 3 years ago
- Model Agnostic Counterfactual Explanations☆86Updated last year