Pinned Repositories
CARE
CARE: Coherent Actionable Recourse based on Sound Counterfactual Explanations
categorical_locality
Interpreting Categorical Data Classifiers using Explanation-based Locality
debug-ml-iclr2019.github.io
Website for debugging machine learning workshop at ICLR 2019
EXPLAN
EXPLAN: Explaining Black-box Classifiers using Adaptive Neighborhood Generation
lime
Lime: Explaining the predictions of any machine learning classifier
meaningful_locality
Meaningful Data Sampling for a Faithful Local Explanation Method
peymanrasouli.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
RobustML
Analyzing and Improving the Robustness of Tabular Classifiers using Counterfactual Explanations
shap
A game theoretic approach to explain the output of any machine learning model.
XdebugML
Explainable Debugger for Black-box Machine Learning Models
peymanrasouli's Repositories
peymanrasouli/CARE
CARE: Coherent Actionable Recourse based on Sound Counterfactual Explanations
peymanrasouli/meaningful_locality
Meaningful Data Sampling for a Faithful Local Explanation Method
peymanrasouli/RobustML
Analyzing and Improving the Robustness of Tabular Classifiers using Counterfactual Explanations
peymanrasouli/EXPLAN
EXPLAN: Explaining Black-box Classifiers using Adaptive Neighborhood Generation
peymanrasouli/XdebugML
Explainable Debugger for Black-box Machine Learning Models
peymanrasouli/categorical_locality
Interpreting Categorical Data Classifiers using Explanation-based Locality
peymanrasouli/debug-ml-iclr2019.github.io
Website for debugging machine learning workshop at ICLR 2019
peymanrasouli/lime
Lime: Explaining the predictions of any machine learning classifier
peymanrasouli/peymanrasouli.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
peymanrasouli/shap
A game theoretic approach to explain the output of any machine learning model.