grazianomita / machine_learning_interpretability_papers
This is a public collection of papers related to machine learning model interpretability.
☆26Updated 3 years ago
Alternatives and similar repositories for machine_learning_interpretability_papers:
Users that are interested in machine_learning_interpretability_papers are comparing it to the libraries listed below
- Supervised Local Modeling for Interpretability☆28Updated 6 years ago
- ☆125Updated 3 years ago
- This is a benchmark to evaluate machine learning local explanaitons quality generated from any explainer for text and image data☆30Updated 3 years ago
- Contrastive Explanation (Foil Trees), developed at TNO/Utrecht University☆45Updated 2 years ago
- Code for reproducing results in Delayed Impact of Fair Machine Learning (Liu et al 2018)☆14Updated 2 years ago
- Implementation of linear CorEx and temporal CorEx.☆37Updated 3 years ago
- Using / reproducing DAC from the paper "Disentangled Attribution Curves for Interpreting Random Forests and Boosted Trees"☆27Updated 4 years ago
- A lightweight implementation of removal-based explanations for ML models.☆59Updated 3 years ago
- Code and data for the experiments in "On Fairness and Calibration"☆51Updated 2 years ago
- Code/figures in Right for the Right Reasons☆55Updated 4 years ago
- Bayesian or-of-and☆34Updated 3 years ago
- Train a simple convnet on the MNIST dataset and evaluate the BALD acquisition function☆16Updated 7 years ago
- Preprint/draft article/blog on some explainable machine learning misconceptions. WIP!☆28Updated 5 years ago
- Interpreting neural networks via the STREAK algorithm (streaming weak submodular maximization)☆23Updated 7 years ago
- PyTorch port and extension of the Deep Bayesian Bandits Library☆42Updated 5 years ago
- Code for "Neural causal learning from unknown interventions"☆99Updated 4 years ago
- Codebase for "Deep Learning for Case-based Reasoning through Prototypes: A Neural Network that Explains Its Predictions" (to appear in AA…☆74Updated 7 years ago
- Implementation of Counterfactual risk minimization☆26Updated 7 years ago
- Algorithms for abstention, calibration and domain adaptation to label shift.☆36Updated 4 years ago
- Uncertainty in Conditional Average Treatment Effect Estimation☆30Updated 4 years ago
- ☆61Updated 2 years ago
- Code for "Evaluating Explainable AI: Which Algorithmic Explanations Help Users Predict Model Behavior?"☆46Updated last year
- Tools for training explainable models using attribution priors.☆123Updated 4 years ago
- Automatic feature engineering using Generative Adversarial Networks using TensorFlow.☆51Updated 2 years ago
- Computing various norms/measures on over-parametrized neural networks☆49Updated 6 years ago
- ☆26Updated 5 years ago
- Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)☆128Updated 3 years ago
- Context Selection for Embedding Models☆27Updated 7 years ago
- Code for our ICML '19 paper: Neural Network Attributions: A Causal Perspective.☆51Updated 3 years ago
- ☆29Updated 6 years ago