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Additive models

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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
Data Science with LLMs and Interpretable ModelsCode2
GAMI-Net: An Explainable Neural Network based on Generalized Additive Models with Structured InteractionsCode2
CAT: Interpretable Concept-based Taylor Additive ModelsCode1
The Intelligible and Effective Graph Neural Additive NetworksCode1
IGANN Sparse: Bridging Sparsity and Interpretability with Non-linear InsightCode1
GeoShapley: A Game Theory Approach to Measuring Spatial Effects in Machine Learning ModelsCode1
Regionally Additive Models: Explainable-by-design models minimizing feature interactionsCode1
LLMs Understand Glass-Box Models, Discover Surprises, and Suggest RepairsCode1
GAM Coach: Towards Interactive and User-centered Algorithmic RecourseCode1
Structural Neural Additive Models: Enhanced Interpretable Machine LearningCode1
Neural Additive Models for Location Scale and Shape: A Framework for Interpretable Neural Regression Beyond the MeanCode1
Additive Covariance Matrix Models: Modelling Regional Electricity Net-Demand in Great BritainCode1
Augmenting Interpretable Models with LLMs during TrainingCode1
From Shapley Values to Generalized Additive Models and backCode1
ControlBurn: Nonlinear Feature Selection with Sparse Tree EnsemblesCode1
How trial-to-trial learning shapes mappings in the mental lexicon: Modelling Lexical Decision with Linear Discriminative LearningCode1
Neural Basis Models for InterpretabilityCode1
Scalable Interpretability via PolynomialsCode1
Deletion and Insertion Tests in Regression ModelsCode1
Fast Sparse Classification for Generalized Linear and Additive ModelsCode1
Fast Interpretable Greedy-Tree SumsCode1
GAM Changer: Editing Generalized Additive Models with Interactive VisualizationCode1
NODE-GAM: Neural Generalized Additive Model for Interpretable Deep LearningCode1
High-Dimensional Bayesian Optimization via Tree-Structured Additive ModelsCode1
Interpretable Machine Learning with an Ensemble of Gradient Boosting MachinesCode1
How Interpretable and Trustworthy are GAMs?Code1
Neural Additive Models: Interpretable Machine Learning with Neural NetsCode1
Semi-Structured Distributional Regression -- Extending Structured Additive Models by Arbitrary Deep Neural Networks and Data ModalitiesCode1
High-Dimensional Bayesian Optimization via Additive Models with Overlapping GroupsCode1
The Most Important Features in Generalized Additive Models Might Be Groups of Features—0
An Optimized Franz-Parisi Criterion and its Equivalence with SQ Lower Bounds—0
Learning Joint Interventional Effects from Single-Variable Interventions in Additive Models—0
neuralGAM: An R Package for Fitting Generalized Additive Neural Networks—0
Navigating the Rashomon Effect: How Personalization Can Help Adjust Interpretable Machine Learning Models to Individual Users—0
Recursive Identification of Structured Systems: An Instrumental-Variable Approach Applied to Mechanical Systems—0
Challenges in interpretability of additive models—0
Adaptive Shrinkage Estimation For Personalized Deep Kernel Regression In Modeling Brain TrajectoriesCode0
Identification of additive multivariable continuous-time systems—0
AutoML Algorithms for Online Generalized Additive Model Selection: Application to Electricity Demand Forecasting—0
MT-NAM: An Efficient and Adaptive Model for Epileptic Seizure Detection—0
Gradient-free stochastic optimization for additive models—0
InstaSHAP: Interpretable Additive Models Explain Shapley Values Instantly—0
Forecasting time series with constraintsCode0
Normative Cerebral Perfusion Across the Lifespan—0
LucidAtlas: Learning Uncertainty-Aware, Covariate-Disentangled, Individualized Atlas Representations—0
Causal Additive Models with Unobserved Causal Paths and Backdoor Paths—0
Variable Selection Methods for Multivariate, Functional, and Complex Biomedical Data in the AI Age—0
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