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Additive models

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TitleStatusHype
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
LucidAtlas: Learning Uncertainty-Aware, Covariate-Disentangled, Individualized Atlas Representations—0
Normative Cerebral Perfusion Across the Lifespan—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
How Your Location Relates to Health: Variable Importance and Interpretable Machine Learning for Environmental and Sociodemographic DataCode0
High-Dimensional Markov-switching Ordinary Differential Processes—0
Automated Demand Forecasting in small to medium-sized enterprises—0
Interpretable Generalized Additive Models for Datasets with Missing ValuesCode0
Meta-learning Loss Functions of Parametric Partial Differential Equations Using Physics-Informed Neural Networks—0
DNAMite: Interpretable Calibrated Survival Analysis with Discretized Additive ModelsCode0
Progression: an extrapolation principle for regression—0
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