Neural Additive Models: Interpretable Machine Learning with Neural Nets

29 April 2020

Papers citing "Neural Additive Models: Interpretable Machine Learning with Neural Nets"

50 / 57 papers shown

Title
neuralGAM: An R Package for Fitting Generalized Additive Neural Networks Ines Ortega-Fernandez Marta Sestelo 26 0 0 13 May 2025
Explainable Neural Networks with Guarantees: A Sparse Estimation Approach Antoine Ledent Peng Liu FAtt 99 0 0 20 Feb 2025
Forecasting time series with constraints Nathan Doumèche Francis Bach Éloi Bedek Gérard Biau Claire Boyer Y. Goude AI4TS 40 0 0 14 Feb 2025
A Hessian-informed hyperparameter optimization for differential learning rate Shiyun Xu Zhiqi Bu Yiliang Zhang Ian J. Barnett 39 1 0 12 Jan 2025
Multi-Scale Grouped Prototypes for Interpretable Semantic Segmentation Hugo Porta Emanuele Dalsasso Diego Marcos D. Tuia 93 0 0 14 Sep 2024
Breaking Neural Network Scaling Laws with Modularity Akhilan Boopathy Sunshine Jiang William Yue Jaedong Hwang Abhiram Iyer Ila Fiete OOD 34 2 0 09 Sep 2024
SoftCVI: Contrastive variational inference with self-generated soft labels Daniel Ward Mark Beaumont Matteo Fasiolo BDL 45 0 0 22 Jul 2024
Feature Inference Attack on Shapley Values Xinjian Luo Yangfan Jiang X. Xiao AAML FAtt 30 19 0 16 Jul 2024
Restyling Unsupervised Concept Based Interpretable Networks with Generative Models Jayneel Parekh Quentin Bouniot Pavlo Mozharovskyi A. Newson Florence dÁlché-Buc SSL 55 1 0 01 Jul 2024
KAN: Kolmogorov-Arnold Networks Ziming Liu Yixuan Wang Sachin Vaidya Fabian Ruehle James Halverson Marin Soljacic Thomas Y. Hou Max Tegmark 72 470 0 30 Apr 2024
Interpretable Prediction and Feature Selection for Survival Analysis Mike Van Ness Madeleine Udell 34 2 0 23 Apr 2024
Neural Additive Image Model: Interpretation through Interpolation Arik Reuter Anton Thielmann Benjamin Saefken DiffM 22 1 0 06 Mar 2024
Implementing local-explainability in Gradient Boosting Trees: Feature Contribution Ángel Delgado-Panadero Beatriz Hernández-Lorca María Teresa García-Ordás J. Benítez-Andrades 32 52 0 14 Feb 2024
Modeling non-linear Effects with Neural Networks in Relational Event Models Edoardo Filippi-Mazzola Ernst C. Wit 19 1 0 19 Dec 2023
Theoretical Evaluation of Asymmetric Shapley Values for Root-Cause Analysis Domokos M. Kelen M. Petreczky Péter Kersch András A. Benczúr FAtt 16 3 0 15 Oct 2023
Towards Faithful Neural Network Intrinsic Interpretation with Shapley Additive Self-Attribution Ying Sun Hengshu Zhu Huixia Xiong TDI FAtt MILM 20 1 0 27 Sep 2023
SurvBeX: An explanation method of the machine learning survival models based on the Beran estimator Lev V. Utkin Danila Eremenko A. Konstantinov 30 4 0 07 Aug 2023
The future of human-centric eXplainable Artificial Intelligence (XAI) is not post-hoc explanations Vinitra Swamy Jibril Frej Tanja Kaser 23 14 0 01 Jul 2023
Self-Reinforcement Attention Mechanism For Tabular Learning Kodjo Mawuena Amekoe M. Dilmi Hanene Azzag M. Lebbah Zaineb Chelly Dagdia Gregoire Jaffre 30 0 0 19 May 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 14 6 0 19 May 2023
How to address monotonicity for model risk management? Dangxing Chen Weicheng Ye 16 5 0 28 Apr 2023
An Interpretable Loan Credit Evaluation Method Based on Rule Representation Learner Zi-yu Chen Xiaomeng Wang Yuanjiang Huang Tao Jia 26 1 0 03 Apr 2023
DeforestVis: Behavior Analysis of Machine Learning Models with Surrogate Decision Stumps Angelos Chatzimparmpas Rafael M. Martins A. Telea Andreas Kerren 16 1 0 31 Mar 2023
An interpretable neural network-based non-proportional odds model for ordinal regression Akifumi Okuno Kazuharu Harada 22 1 0 31 Mar 2023
Exploring and Interacting with the Set of Good Sparse Generalized Additive Models Chudi Zhong Zhi Chen Jiachang Liu Margo Seltzer Cynthia Rudin 28 11 0 28 Mar 2023
LEURN: Learning Explainable Univariate Rules with Neural Networks Çağlar Aytekin FAtt 27 0 0 27 Mar 2023
NAISR: A 3D Neural Additive Model for Interpretable Shape Representation Yining Jiao C. Zdanski Julia Kimbell Andrew Prince Cameron P Worden ... Christopher Rutter Benjamin Shields William Dunn Jisan Mahmud Marc Niethammer 34 3 0 16 Mar 2023
Structural Neural Additive Models: Enhanced Interpretable Machine Learning Mattias Luber Anton Thielmann Benjamin Säfken 16 7 0 18 Feb 2023
Bort: Towards Explainable Neural Networks with Bounded Orthogonal Constraint Borui Zhang Wenzhao Zheng Jie Zhou Jiwen Lu AAML 23 7 0 18 Dec 2022
Interpretability with full complexity by constraining feature information Kieran A. Murphy Danielle Bassett FAtt 27 5 0 30 Nov 2022
Extending the Neural Additive Model for Survival Analysis with EHR Data M. Peroni Marharyta Kurban Sun-Young Yang Young Sun Kim H. Kang J. Song 17 6 0 15 Nov 2022
Higher-order Neural Additive Models: An Interpretable Machine Learning Model with Feature Interactions Minkyu Kim Hyunjin Choi Jinho Kim FAtt 30 8 0 30 Sep 2022
Interpretable Selective Learning in Credit Risk Dangxing Chen Weicheng Ye Jiahui Ye FaML 22 14 0 21 Sep 2022
Monotonic Neural Additive Models: Pursuing Regulated Machine Learning Models for Credit Scoring Dangxing Chen Weicheng Ye FaML 18 13 0 21 Sep 2022
Making the black-box brighter: interpreting machine learning algorithm for forecasting drilling accidents E. Gurina Nikita Klyuchnikov Ksenia Antipova D. Koroteev FAtt 25 8 0 06 Sep 2022
A Scalable, Interpretable, Verifiable & Differentiable Logic Gate Convolutional Neural Network Architecture From Truth Tables Adrien Benamira Tristan Guérand Thomas Peyrin Trevor Yap Bryan Hooi 32 1 0 18 Aug 2022
Open Source Vizier: Distributed Infrastructure and API for Reliable and Flexible Blackbox Optimization Xingyou Song Sagi Perel Chansoo Lee Greg Kochanski Daniel Golovin 23 26 0 27 Jul 2022
Why do tree-based models still outperform deep learning on tabular data? Léo Grinsztajn Edouard Oyallon Gaël Varoquaux LMTD 22 355 0 18 Jul 2022
Using Model-Based Trees with Boosting to Fit Low-Order Functional ANOVA Models Linwei Hu Jie Chen V. Nair 19 3 0 14 Jul 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 54 27 0 30 Jun 2022
Interpretable Deep Causal Learning for Moderation Effects A. Caron G. Baio I. Manolopoulou CML OOD 19 2 0 21 Jun 2022
Neural Basis Models for Interpretability Filip Radenovic Abhimanyu Dubey D. Mahajan FAtt 19 46 0 27 May 2022
ExSpliNet: An interpretable and expressive spline-based neural network Daniele Fakhoury Emanuele Fakhoury H. Speleers 11 33 0 03 May 2022
Using Decision Tree as Local Interpretable Model in Autoencoder-based LIME Niloofar Ranjbar Reza Safabakhsh FAtt 8 5 0 07 Apr 2022
Sparse Neural Additive Model: Interpretable Deep Learning with Feature Selection via Group Sparsity Shiyun Xu Zhiqi Bu Pratik Chaudhari Ian J. Barnett 14 21 0 25 Feb 2022
Overview frequency principle/spectral bias in deep learning Z. Xu Yaoyu Zhang Tao Luo FaML 25 65 0 19 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
Self-Interpretable Model with TransformationEquivariant Interpretation Yipei Wang Xiaoqian Wang 24 23 0 09 Nov 2021
Deep Neural Networks and Tabular Data: A Survey V. Borisov Tobias Leemann Kathrin Seßler Johannes Haug Martin Pawelczyk Gjergji Kasneci LMTD 22 645 0 05 Oct 2021
LocalGLMnet: interpretable deep learning for tabular data Ronald Richman M. Wüthrich LMTD FAtt 20 27 0 23 Jul 2021