JOSS Papers: explainability

All Papers
1885
 Published Papers
1676
 Active Papers
209
published Published 7 months ago

TX$^2$: Transformer eXplainability and eXploration

Python
@WildfireXIII
10.21105/joss.03652
published Published about 1 year ago

imodels: a python package for fitting interpretable models

Python Jupyter Notebook
@csinva
10.21105/joss.03192
published Published over 2 years ago

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

R Python C++
@martinju
10.21105/joss.02027
published Published over 2 years ago

modelStudio: Interactive Studio with Explanations for ML Predictive Models

R JavaScript
@hbaniecki
10.21105/joss.01798
published Published about 3 years ago

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

R
@matiszak
10.21105/joss.01444
published Published about 3 years ago

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

Python JavaScript Jupyter Notebook
@kmichael08
10.21105/joss.01389
published Published over 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