JOSS Papers: explainability

Published Papers

published Published about 1 month ago

TX$^2$: Transformer eXplainability and eXploration

Python

10.21105/joss.03652

published Published 9 months ago

imodels: a python package for fitting interpretable models

Python Jupyter Notebook

10.21105/joss.03192

published Published almost 2 years ago

shapr: An R-package for explaining machine learning models with dependence-aware Shapley values

R Python C++

10.21105/joss.02027

published Published about 2 years ago

modelStudio: Interactive Studio with Explanations for ML Predictive Models

R JavaScript

10.21105/joss.01798

published Published over 2 years ago

modelDown: automated website generator with interpretable documentation for predictive machine learning models

R

10.21105/joss.01444

published Published over 2 years ago

pyCeterisParibus: explaining Machine Learning models with Ceteris Paribus Profiles in Python

Python JavaScript Jupyter Notebook

10.21105/joss.01389

published Published about 3 years ago

survxai: an R package for structure-agnostic explanations of survival models

R

@AleksandraDabrowska

10.21105/joss.00961

Displaying all 7 papers

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ISSN 2475-9066