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Additive models

Papers

Showing 76–100 of 252 papers

TitleStatusHype
Can local explanation techniques explain linear additive models?Code0
LLMs Understand Glass-Box Models, Discover Surprises, and Suggest RepairsCode1
Improving Neural Additive Models with Bayesian PrinciplesCode0
Curve Your Enthusiasm: Concurvity Regularization in Differentiable Generalized Additive ModelsCode0
Representing Additive Gaussian Processes by Sparse Matrices—0
How to address monotonicity for model risk management?—0
The Structurally Complex with Additive Parent Causality (SCARY) DatasetCode0
Minimax Signal Detection in Sparse Additive Models—0
Causal Discovery with Score Matching on Additive Models with Arbitrary Noise—0
Exploring and Interacting with the Set of Good Sparse Generalized Additive ModelsCode0
Interpretable Reinforcement Learning via Neural Additive Models for Inventory Management—0
GAM Coach: Towards Interactive and User-centered Algorithmic RecourseCode1
Structural Neural Additive Models: Enhanced Interpretable Machine LearningCode1
Nowcasting the 2022 mpox outbreak in EnglandCode0
Approximately Bayes-Optimal Pseudo Label Selection—0
Frugal day-ahead forecasting of multiple local electricity loads by aggregating adaptive models—0
Neural Additive Models for Location Scale and Shape: A Framework for Interpretable Neural Regression Beyond the MeanCode1
Monotonicity for AI ethics and society: An empirical study of the monotonic neural additive model in criminology, education, health care, and finance—0
Extractive Text Summarization Using Generalized Additive Models with Interactions for Sentence Selection—0
Classification by sparse generalized additive models—0
Ensemble Multi-Quantiles: Adaptively Flexible Distribution Prediction for Uncertainty QuantificationCode0
Estimating Discontinuous Time-Varying Risk Factors and Treatment Benefits for COVID-19 with Interpretable ML—0
Additive Covariance Matrix Models: Modelling Regional Electricity Net-Demand in Great BritainCode1
Rethinking Log Odds: Linear Probability Modelling and Expert Advice in Interpretable Machine Learning—0
Individualized and Global Feature Attributions for Gradient Boosted Trees in the Presence of _2 RegularizationCode0
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