Skip to content

EoinKenny/IJCAI-2019

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

17 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

IJCAI-2019: Twin-Systems to Explain Artificial Neural Networks Using Case-Based Reasoning

This repository is the official implementation for the above IJCAI paper.

An updated version of the algorithm and user studies was recently published at the Artificial Intelligence Journal. It is recommended you refer to this article. I made a colab file which you can use to see the most up-to-date version of the twin system algorithm here:

SEE UP-TO-DATE VERSION OF TWIN-SYSTEM ALGORITHM HERE

alt text

Requirements

To install requirements:

python3 -m venv myenv
source myenv/bin/activate
pip install -r requirements.txt

Generating An Explanation

Follow the notebooks one by one to go through the experiments and recreate the results of the main paper.

alt text

alt text

Results

Table of results from experiment 2 using CNNs:

alt text

Cite Bibtext

@inproceedings{ijcai2019-376, title = {Twin-Systems to Explain Artificial Neural Networks using Case-Based Reasoning: Comparative Tests of Feature-Weighting Methods in ANN-CBR Twins for XAI}, author = {Kenny, Eoin M. and Keane, Mark T.}, booktitle = {Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, {IJCAI-19}}, publisher = {International Joint Conferences on Artificial Intelligence Organization},
pages = {2708--2715}, year = {2019}, month = {7}, doi = {10.24963/ijcai.2019/376}, url = {https://doi.org/10.24963/ijcai.2019/376}, }

}

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published