The many Shapley values for model explanation

22 August 2019

Papers citing "The many Shapley values for model explanation"

20 / 20 papers shown

Title
Computing Exact Shapley Values in Polynomial Time for Product-Kernel Methods Majid Mohammadi Siu Lun Chau Krikamol Muandet FAtt 37 0 0 22 May 2025
Probabilistic Stability Guarantees for Feature Attributions Helen Jin Anton Xue Weiqiu You Surbhi Goel Eric Wong 40 0 0 18 Apr 2025
Investigating the Duality of Interpretability and Explainability in Machine Learning Moncef Garouani Josiane Mothe Ayah Barhrhouj Julien Aligon AAML 54 2 0 27 Mar 2025
Surrogate Modeling for Explainable Predictive Time Series Corrections Alfredo Lopez Florian Sobieczky AI4TS 62 0 0 17 Jan 2025
Unifying Feature-Based Explanations with Functional ANOVA and Cooperative Game Theory Fabian Fumagalli Maximilian Muschalik Eyke Hüllermeier Barbara Hammer J. Herbinger FAtt 55 2 0 22 Dec 2024
A Comprehensive Study of Shapley Value in Data Analytics Hong Lin Shixin Wan Zhongle Xie Ke Chen Meihui Zhang Lidan Shou Gang Chen 115 0 0 02 Dec 2024
T-Explainer: A Model-Agnostic Explainability Framework Based on Gradients Evandro S. Ortigossa Fábio F. Dias Brian Barr Claudio T. Silva L. G. Nonato FAtt 70 2 0 25 Apr 2024
Explaining Quantum Circuits with Shapley Values: Towards Explainable Quantum Machine Learning R. Heese Thore Gerlach Sascha Mucke Sabine Muller Matthias Jakobs Nico Piatkowski 29 18 0 22 Jan 2023
Measuring the Driving Forces of Predictive Performance: Application to Credit Scoring Hué Sullivan Hurlin Christophe Pérignon Christophe Saurin Sébastien 35 0 0 12 Dec 2022
On the Tractability of SHAP Explanations Guy Van den Broeck A. Lykov Maximilian Schleich Dan Suciu FAtt TDI 39 266 0 18 Sep 2020
Explainability in Deep Reinforcement Learning Alexandre Heuillet Fabien Couthouis Natalia Díaz Rodríguez XAI 40 279 0 15 Aug 2020
Explainable AI for a No-Teardown Vehicle Component Cost Estimation: A Top-Down Approach A. Moawad E. Islam Namdoo Kim R. Vijayagopal A. Rousseau Wei Biao Wu 36 5 0 15 Jun 2020
Feature relevance quantification in explainable AI: A causal problem Dominik Janzing Lenon Minorics Patrick Blobaum FAtt CML 26 279 0 29 Oct 2019
Explaining individual predictions when features are dependent: More accurate approximations to Shapley values K. Aas Martin Jullum Anders Løland FAtt TDI 38 610 0 25 Mar 2019
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Jacob Devlin Ming-Wei Chang Kenton Lee Kristina Toutanova VLM SSL SSeg 364 93,936 0 11 Oct 2018
Consistent Individualized Feature Attribution for Tree Ensembles Scott M. Lundberg G. Erion Su-In Lee FAtt TDI 37 1,379 0 12 Feb 2018
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 36 21,459 0 22 May 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 52 5,920 0 04 Mar 2017
On Shapley value for measuring importance of dependent inputs Art B. Owen Clémentine Prieur FAtt TDI 33 149 0 06 Oct 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 100 16,765 0 16 Feb 2016