JOSS Papers: interpretability

Published Papers

published Published about 2 months ago

TelescopeML -- I. An End-to-End Python Package for Interpreting Telescope Datasets through Training Machine Learning Models, Generating Statistical Reports, and Visualizing Results

Python

@EhsanGharibNezhad

10.21105/joss.06346

published Published 9 months ago

CRE: An R package for interpretable discovery and inference of heterogeneous treatment effects

R

10.21105/joss.05587

published Published 9 months ago

HNN-core: A Python software for cellular and circuit-level interpretation of human MEG/EEG

Python Jupyter Notebook AMPL

10.21105/joss.05848

published Published 9 months ago

pudu: A Python library for agnostic feature selection and explainability of Machine Learning spectroscopic problems

Python

10.21105/joss.05873

published Published 11 months ago

SIRUS.jl: Interpretable Machine Learning via Rule Extraction

Julia

10.21105/joss.05786

published Published over 1 year ago

TSInterpret: A Python Package for the Interpretability of Time Series Classification

Python

10.21105/joss.05220

published Published over 1 year ago

OpenRepGrid.ic: A software for Interpretive Clustering

R

10.21105/joss.03292

published Published about 3 years ago

starry_process: Interpretable Gaussian processes for stellar light curves

Python C++ C

10.21105/joss.03071

published Published over 3 years ago

imodels: a python package for fitting interpretable models

Python Jupyter Notebook

10.21105/joss.03192

published Published over 4 years ago

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

R Python C++

10.21105/joss.02027

Displaying papers 1 - 10 of 21 in total

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