NODE-GAM: Neural Generalized Additive Model for Interpretable Deep
Learning

NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning

3 June 2021

Anna Goldenberg

Papers citing "NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning"

15 / 15 papers shown

Title
Error-controlled non-additive interaction discovery in machine learning models Winston Chen Yifan Jiang William Stafford Noble Yang Young Lu 45 1 0 17 Feb 2025
Linear Mode Connectivity in Differentiable Tree Ensembles Ryuichi Kanoh M. Sugiyama 72 1 0 17 Feb 2025
Interpretable Prediction and Feature Selection for Survival Analysis Mike Van Ness Madeleine Udell 39 2 0 23 Apr 2024
Neural Additive Image Model: Interpretation through Interpolation Arik Reuter Anton Thielmann Benjamin Saefken DiffM 34 1 0 06 Mar 2024
Multi-Objective Optimization of Performance and Interpretability of Tabular Supervised Machine Learning Models Lennart Schneider B. Bischl Janek Thomas 30 6 0 17 Jul 2023
Backpack Language Models John Hewitt John Thickstun Christopher D. Manning Percy Liang KELM 13 16 0 26 May 2023
Self-Reinforcement Attention Mechanism For Tabular Learning Kodjo Mawuena Amekoe M. Dilmi Hanene Azzag M. Lebbah Zaineb Chelly Dagdia Gregoire Jaffre 37 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 19 6 0 19 May 2023
Structural Neural Additive Models: Enhanced Interpretable Machine Learning Mattias Luber Anton Thielmann Benjamin Säfken 31 7 0 18 Feb 2023
Neural Additive Models for Location Scale and Shape: A Framework for Interpretable Neural Regression Beyond the Mean Anton Thielmann René-Marcel Kruse Thomas Kneib Benjamin Säfken 29 12 0 27 Jan 2023
Interpretability with full complexity by constraining feature information Kieran A. Murphy Danielle Bassett FAtt 27 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 35 8 0 30 Sep 2022
Neural Basis Models for Interpretability Filip Radenovic Abhimanyu Dubey D. Mahajan FAtt 24 46 0 27 May 2022
Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data Sergei Popov S. Morozov Artem Babenko LMTD 88 294 0 13 Sep 2019
Quasi-hyperbolic momentum and Adam for deep learning Jerry Ma Denis Yarats ODL 84 129 0 16 Oct 2018