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#p-nagler

LPB+26b

Cost-Effectiveness of AI-Assisted Detection of Apical Periodontitis on Panoramic Radiographs

International Endodontic Journal. Mar. 2026

#p-nagler

LNC26

Scandinavian Actuarial Journal. Mar. 2026

#p-nagler

BN26

Fast Rates for Nonstationary Weighted Risk Minimization

Preprint (Feb. 2026)

#p-nagler

NBP26

Online Bootstrap Inference for the Trend of Nonstationary Time Series

Preprint (Feb. 2026)

#p-nagler

NL26

Optimal Neural Network Approximation of Smooth Compositional Functions on Sets With Low Intrinsic Dimension

Preprint (Feb. 2026)

#p-nagler

Nag25

Simplified Vine Copula Models: State of Science and Affairs

Risk Sciences 1.100022. Dec. 2025

#p-nagler

GN25

Properties of Stepwise Parameter Estimation in High-Dimensional Vine Copulas

Preprint (Nov. 2025)

#p-nagler

VN25

Throwing Vines at the Wall: Structure Learning via Random Search

Preprint (Oct. 2025)

#p-nagler

HWN+25

Decomposing Global Feature Effects Based on Feature Interactions

ECML-PKDD 2025

#p-bischl #p-nagler

FLK+25

Towards More Realistic Climate Model Outputs: A Multivariate Bias Correction Based on Zero-Inflated Vine Copulas

Journal of the Royal Statistical Society. Series C (Applied Statistics).qlaf044. Aug. 2025

#p-kuechenhoff #p-nagler

AKN+25

Hybrid Bernstein Normalizing Flows for Flexible Multivariate Density Regression With Interpretable Marginals

UAI 2025

#p-nagler #p-ruegamer

SRN25

Adjustment for Confounding Using Pre-Trained Representations

ICML 2025

#p-nagler #p-ruegamer

PP25

PROBLEM-TAILORED MULTI-OBJECTIVE OPTIMIZATION ALGORITHM CONSTRUCTION by PARETO REFLECTIONS

Journal of Mathematical Sciences. Jul. 2025

#p-nagler

WBL+25a

Predictive Modeling for Step II Therapy Response in Periodontitis - Model Development and Validation

npj Digital Medicine 8.445. Jul. 2025

#p-bischl #p-nagler

CVN+25

Vine Copulas as Differentiable Computational Graphs

Preprint (Jun. 2025)

#p-nagler

MLN+25

Assessing Climate-Driven Mortality Risk: A Stochastic Approach With Distributed Lag Non-Linear Models

Preprint (Jun. 2025)

#p-nagler #p-navab

DKP+25

Paths and Ambient Spaces in Neural Loss Landscapes

AISTATS 2025

#p-nagler #p-ruegamer

NV25

Solving Estimating Equations With Copulas

Invited Talk @AISTATS 2025

#p-nagler

NR25

Uncertainty Quantification for Prior-Fitted Networks Using Martingale Posteriors

Workshop @AABI 2025

#p-nagler #p-ruegamer

NR25a

Uncertainty Quantification for Prior-Fitted Networks Using Martingale Posteriors

FPI @ICLR 2025

#p-nagler #p-ruegamer

FLH+25

Modelling Climate Variables at High Temporal Resolution

Preprint (Feb. 2025)

#p-kuechenhoff #p-nagler

SFN+25

Constructing Confidence Intervals for 'The' Generalization Error – A Comprehensive Benchmark Study

Journal of Data-Centric Machine Learning Research 2.6. Jan. 2025

#p-bischl #p-boulesteix #p-nagler

NSB+24

Reshuffling Resampling Splits Can Improve Generalization of Hyperparameter Optimization

NeurIPS 2024

#p-bischl #p-feurer #p-nagler

KNF+24

Towards Localization via Data Embedding for TabPFN

TLR @NeurIPS 2024

#p-feurer #p-nagler

HWN+24

Decomposing Global Feature Effects Based on Feature Interactions

Journal of Machine Learning Research 25.381. Dec. 2024

#p-bischl #p-nagler

GN24

Asymptotics for Estimating a Diverging Number of Parameters -- With and Without Sparsity

Preprint (Nov. 2024)

#p-nagler

RKW+24

Generalizing Orthogonalization for Models With Non-Linearities

ICML 2024

#p-bischl #p-nagler #p-ruegamer

RKC+24

Interpretable Machine Learning for TabPFN

XAI 2024

#p-bischl #p-feurer #p-nagler #p-ruegamer

SHL+24

Label-Wise Aleatoric and Epistemic Uncertainty Quantification

UAI 2024

#p-bischl #p-huellermeier #p-nagler

PN24

An Online Bootstrap for Time Series

AISTATS 2024

#p-nagler

SHW+23

Second-Order Uncertainty Quantification: Variance-Based Measures

Preprint (Dec. 2023)

#p-bischl #p-huellermeier #p-nagler

RGD+23

Approximately Bayes-Optimal Pseudo-Label Selection

UAI 2023

#p-bischl #p-nagler

Nag23

Statistical Foundations of Prior-Data Fitted Networks

ICML 2023

#p-nagler

NV23

Solving Estimating Equations With Copulas

Journal of the American Statistical Association 119.546. Mar. 2023

#p-nagler

LNR22

Modeling Stochastic Data Using Copulas for Applications in the Validation of Autonomous Driving

Electronics 11.24. Dec. 2022

#p-nagler

PSP22

Parameter Individual Optimal Experimental Design and Calibration of Parametric Models

IEEE Access 10. Oct. 2022

#p-nagler

#p-nagler

Cost-Effectiveness of AI-Assisted Detection of Apical Periodontitis on Panoramic Radiographs

Modeling Cold-Related Excess Deaths via Stationary Vine Copulas

Fast Rates for Nonstationary Weighted Risk Minimization

Online Bootstrap Inference for the Trend of Nonstationary Time Series

Optimal Neural Network Approximation of Smooth Compositional Functions on Sets With Low Intrinsic Dimension

Simplified Vine Copula Models: State of Science and Affairs

Properties of Stepwise Parameter Estimation in High-Dimensional Vine Copulas

Throwing Vines at the Wall: Structure Learning via Random Search

Decomposing Global Feature Effects Based on Feature Interactions

Towards More Realistic Climate Model Outputs: A Multivariate Bias Correction Based on Zero-Inflated Vine Copulas

Hybrid Bernstein Normalizing Flows for Flexible Multivariate Density Regression With Interpretable Marginals

Adjustment for Confounding Using Pre-Trained Representations

PROBLEM-TAILORED MULTI-OBJECTIVE OPTIMIZATION ALGORITHM CONSTRUCTION by PARETO REFLECTIONS

Predictive Modeling for Step II Therapy Response in Periodontitis - Model Development and Validation

Vine Copulas as Differentiable Computational Graphs

Assessing Climate-Driven Mortality Risk: A Stochastic Approach With Distributed Lag Non-Linear Models

Paths and Ambient Spaces in Neural Loss Landscapes

Solving Estimating Equations With Copulas

Uncertainty Quantification for Prior-Fitted Networks Using Martingale Posteriors

Uncertainty Quantification for Prior-Fitted Networks Using Martingale Posteriors

Modelling Climate Variables at High Temporal Resolution

Constructing Confidence Intervals for 'The' Generalization Error – A Comprehensive Benchmark Study

Reshuffling Resampling Splits Can Improve Generalization of Hyperparameter Optimization

Towards Localization via Data Embedding for TabPFN

Decomposing Global Feature Effects Based on Feature Interactions

Asymptotics for Estimating a Diverging Number of Parameters -- With and Without Sparsity

Generalizing Orthogonalization for Models With Non-Linearities

Interpretable Machine Learning for TabPFN

Label-Wise Aleatoric and Epistemic Uncertainty Quantification

An Online Bootstrap for Time Series

Second-Order Uncertainty Quantification: Variance-Based Measures

Approximately Bayes-Optimal Pseudo-Label Selection

Statistical Foundations of Prior-Data Fitted Networks

Solving Estimating Equations With Copulas

Modeling Stochastic Data Using Copulas for Applications in the Validation of Autonomous Driving

Parameter Individual Optimal Experimental Design and Calibration of Parametric Models