How Interpretable and Trustworthy are GAMs?

11 June 2020

C. Chang

S. Tan

Benjamin J. Lengerich

Papers citing "How Interpretable and Trustworthy are GAMs?"

21 / 21 papers shown

Title
Challenges in interpretability of additive models Xinyu Zhang Julien Martinelli S. T. John AAML AI4CE 32 1 0 14 Apr 2025
SurvBeX: An explanation method of the machine learning survival models based on the Beran estimator Lev V. Utkin Danila Eremenko A. Konstantinov 32 4 0 07 Aug 2023
Curve Your Enthusiasm: Concurvity Regularization in Differentiable Generalized Additive Models Julien N. Siems Konstantin Ditschuneit Winfried Ripken Alma Lindborg Maximilian Schambach Johannes Otterbach Martin Genzel 24 6 0 19 May 2023
GAM Coach: Towards Interactive and User-centered Algorithmic Recourse Zijie J. Wang J. W. Vaughan R. Caruana Duen Horng Chau HAI 31 21 0 27 Feb 2023
Interpretability with full complexity by constraining feature information Kieran A. Murphy Danielle Bassett FAtt 35 5 0 30 Nov 2022
Higher-order Neural Additive Models: An Interpretable Machine Learning Model with Feature Interactions Minkyu Kim Hyunjin Choi Jinho Kim FAtt 38 8 0 30 Sep 2022
TimberTrek: Exploring and Curating Sparse Decision Trees with Interactive Visualization Zijie J. Wang Chudi Zhong Rui Xin Takuya Takagi Zhi Chen Duen Horng Chau Cynthia Rudin Margo Seltzer 33 14 0 19 Sep 2022
A Concept and Argumentation based Interpretable Model in High Risk Domains Haixiao Chi Dawei Wang Gaojie Cui Feng Mao Beishui Liao 29 1 0 17 Aug 2022
Interpretability, Then What? Editing Machine Learning Models to Reflect Human Knowledge and Values Zijie J. Wang Alex Kale Harsha Nori P. Stella M. Nunnally Duen Horng Chau Mihaela Vorvoreanu J. W. Vaughan R. Caruana KELM 66 27 0 30 Jun 2022
The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations Aparna Balagopalan Haoran Zhang Kimia Hamidieh Thomas Hartvigsen Frank Rudzicz Marzyeh Ghassemi 38 78 0 06 May 2022
Differentially Private Estimation of Heterogeneous Causal Effects Fengshi Niu Harsha Nori B. Quistorff R. Caruana Donald Ngwe A. Kannan CML 25 13 0 22 Feb 2022
Topological Representations of Local Explanations Peter Xenopoulos G. Chan Harish Doraiswamy L. G. Nonato Brian Barr Claudio Silva FAtt 28 4 0 06 Jan 2022
GAM Changer: Editing Generalized Additive Models with Interactive Visualization Zijie J. Wang Alex Kale Harsha Nori P. Stella M. Nunnally Duen Horng Chau Mihaela Vorvoreanu Jennifer Wortman Vaughan R. Caruana KELM 19 24 0 06 Dec 2021
Accuracy, Interpretability, and Differential Privacy via Explainable Boosting Harsha Nori R. Caruana Zhiqi Bu J. Shen Janardhan Kulkarni 33 37 0 17 Jun 2021
A Comprehensive Taxonomy for Explainable Artificial Intelligence: A Systematic Survey of Surveys on Methods and Concepts Gesina Schwalbe Bettina Finzel XAI 34 184 0 15 May 2021
Ensembles of Random SHAPs Lev V. Utkin A. Konstantinov FAtt 16 20 0 04 Mar 2021
Interpretable Machine Learning with an Ensemble of Gradient Boosting Machines A. Konstantinov Lev V. Utkin FedML AI4CE 10 139 0 14 Oct 2020
GAMI-Net: An Explainable Neural Network based on Generalized Additive Models with Structured Interactions Zebin Yang Aijun Zhang Agus Sudjianto FAtt 19 126 0 16 Mar 2020
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 338 4,230 0 23 Aug 2019
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 257 3,696 0 28 Feb 2017
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 207 2,091 0 24 Oct 2016