dtak / rrrLinks
Code/figures in Right for the Right Reasons
☆57Updated 5 years ago
Alternatives and similar repositories for rrr
Users that are interested in rrr are comparing it to the libraries listed below
Sorting:
- ☆135Updated 6 years ago
- Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)☆129Updated 4 years ago
- ☆125Updated 4 years ago
- Tools for training explainable models using attribution priors.☆125Updated 4 years ago
- Code and data for the experiments in "On Fairness and Calibration"☆51Updated 3 years ago
- This is a benchmark to evaluate machine learning local explanaitons quality generated from any explainer for text and image data☆30Updated 4 years ago
- Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" ht…☆128Updated 4 years ago
- Supervised Local Modeling for Interpretability☆29Updated 7 years ago
- Algorithms for abstention, calibration and domain adaptation to label shift.☆37Updated 5 years ago
- Codes for reproducing the contrastive explanation in “Explanations based on the Missing: Towards Contrastive Explanations with Pertinent…☆54Updated 7 years ago
- A lightweight implementation of removal-based explanations for ML models.☆59Updated 4 years ago
- ☆62Updated 4 years ago
- Codebase for "Deep Learning for Case-based Reasoning through Prototypes: A Neural Network that Explains Its Predictions" (to appear in AA…☆76Updated 8 years ago
- Source code for paper Mroueh, Sercu, Rigotti, Padhi, dos Santos, "Sobolev Independence Criterion", NeurIPS 2019☆14Updated last year
- ☆14Updated last year
- Toy datasets to evaluate algorithms for domain generalization and invariance learning.☆43Updated 4 years ago
- The Synbols dataset generator is a ServiceNow Research project that was started at Element AI.☆45Updated 2 years ago
- Experiments for AAAI anchor paper☆66Updated 7 years ago
- Interpreting neural networks via the STREAK algorithm (streaming weak submodular maximization)☆23Updated 8 years ago
- Code for our ICML '19 paper: Neural Network Attributions: A Causal Perspective.☆51Updated 4 years ago
- To Trust Or Not To Trust A Classifier. A measure of uncertainty for any trained (possibly black-box) classifier which is more effective t…☆177Updated 2 years ago
- Combating hidden stratification with GEORGE☆64Updated 4 years ago
- Code for the paper 'Understanding Measures of Uncertainty for Adversarial Example Detection'☆62Updated 7 years ago
- Active and Sample-Efficient Model Evaluation☆26Updated 7 months ago
- python tools to check recourse in linear classification☆77Updated 5 years ago
- Explaining a black-box using Deep Variational Information Bottleneck Approach☆46Updated 3 years ago
- Comparing fairness-aware machine learning techniques.☆160Updated 3 years ago
- code release for the paper "On Completeness-aware Concept-Based Explanations in Deep Neural Networks"☆54Updated 3 years ago
- Code for "Neural causal learning from unknown interventions"☆104Updated 5 years ago
- Python package for evaluating model calibration in classification☆20Updated 6 years ago