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Additive models

Papers

Showing 125 of 252 papers

TitleStatusHype
Interpretability, Then What? Editing Machine Learning Models to Reflect Human Knowledge and ValuesCode5
GAM(e) changer or not? An evaluation of interpretable machine learning models based on additive model constraintsCode5
InterpretML: A Unified Framework for Machine Learning InterpretabilityCode3
GAMI-Net: An Explainable Neural Network based on Generalized Additive Models with Structured InteractionsCode2
Data Science with LLMs and Interpretable ModelsCode2
Interpretable Machine Learning with an Ensemble of Gradient Boosting MachinesCode1
IGANN Sparse: Bridging Sparsity and Interpretability with Non-linear InsightCode1
LLMs Understand Glass-Box Models, Discover Surprises, and Suggest RepairsCode1
GAM Changer: Editing Generalized Additive Models with Interactive VisualizationCode1
Fast Interpretable Greedy-Tree SumsCode1
How Interpretable and Trustworthy are GAMs?Code1
How trial-to-trial learning shapes mappings in the mental lexicon: Modelling Lexical Decision with Linear Discriminative LearningCode1
From Shapley Values to Generalized Additive Models and backCode1
Deletion and Insertion Tests in Regression ModelsCode1
CAT: Interpretable Concept-based Taylor Additive ModelsCode1
Semi-Structured Distributional Regression -- Extending Structured Additive Models by Arbitrary Deep Neural Networks and Data ModalitiesCode1
Additive Covariance Matrix Models: Modelling Regional Electricity Net-Demand in Great BritainCode1
ControlBurn: Nonlinear Feature Selection with Sparse Tree EnsemblesCode1
Augmenting Interpretable Models with LLMs during TrainingCode1
Fast Sparse Classification for Generalized Linear and Additive ModelsCode1
GeoShapley: A Game Theory Approach to Measuring Spatial Effects in Machine Learning ModelsCode1
GAM Coach: Towards Interactive and User-centered Algorithmic RecourseCode1
High-Dimensional Bayesian Optimization via Additive Models with Overlapping GroupsCode1
High-Dimensional Bayesian Optimization via Tree-Structured Additive ModelsCode1
Neural Additive Models for Location Scale and Shape: A Framework for Interpretable Neural Regression Beyond the MeanCode1
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