Synthetic Benchmarks for Scientific Research in Explainable Machine
Learning

Synthetic Benchmarks for Scientific Research in Explainable Machine Learning

23 June 2021

Yang Liu

Sujay Khandagale

Papers citing "Synthetic Benchmarks for Scientific Research in Explainable Machine Learning"

13 / 13 papers shown

Title
Feature Importance Depends on Properties of the Data: Towards Choosing the Correct Explanations for Your Data and Decision Trees based Models Célia Wafa Ayad Thomas Bonnier Benjamin Bosch Sonali Parbhoo Jesse Read FAtt XAI 100 0 0 11 Feb 2025
Beyond the Veil of Similarity: Quantifying Semantic Continuity in Explainable AI Qi Huang Emanuele Mezzi Osman Mutlu Miltiadis Kofinas Vidya Prasad Shadnan Azwad Khan Elena Ranguelova N. V. Stein 45 0 0 17 Jul 2024
Accurate estimation of feature importance faithfulness for tree models Mateusz Gajewski Adam Karczmarz Mateusz Rapicki Piotr Sankowski 37 0 0 04 Apr 2024
Precise Benchmarking of Explainable AI Attribution Methods Rafael Brandt Daan Raatjens G. Gaydadjiev XAI 24 4 0 06 Aug 2023
CoRTX: Contrastive Framework for Real-time Explanation Yu-Neng Chuang Guanchu Wang Fan Yang Quan-Gen Zhou Pushkar Tripathi Xuanting Cai Xia Hu 46 19 0 05 Mar 2023
Explainable AI does not provide the explanations end-users are asking for Savio Rozario G. Cevora XAI 12 0 0 25 Jan 2023
BAGEL: A Benchmark for Assessing Graph Neural Network Explanations Mandeep Rathee Thorben Funke Avishek Anand Megha Khosla 36 14 0 28 Jun 2022
SIBILA: A novel interpretable ensemble of general-purpose machine learning models applied to medical contexts A. Banegas-Luna Horacio Pérez-Sánchez 30 1 0 12 May 2022
The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective Satyapriya Krishna Tessa Han Alex Gu Steven Wu S. Jabbari Himabindu Lakkaraju 177 185 0 03 Feb 2022
Deep Neural Networks and Tabular Data: A Survey V. Borisov Tobias Leemann Kathrin Seßler Johannes Haug Martin Pawelczyk Gjergji Kasneci LMTD 27 645 0 05 Oct 2021
Probing GNN Explainers: A Rigorous Theoretical and Empirical Analysis of GNN Explanation Methods Chirag Agarwal Marinka Zitnik Himabindu Lakkaraju 19 51 0 16 Jun 2021
Fairness in Machine Learning L. Oneto Silvia Chiappa FaML 249 488 0 31 Dec 2020
A Survey on Neural Network Interpretability Yu Zhang Peter Tiño A. Leonardis K. Tang FaML XAI 141 660 0 28 Dec 2020