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#p-ruegamer

PSJ+26

Higher-Order Hit-&-Run Samplers for Linearly Constrained Densities

UAI 2026

#p-ruegamer

SR26a

Position: The Time for Sampling Is Now! Charting a New Course for Bayesian Deep Learning

ICML 2026

#p-ruegamer

Rue26

On the Epistemic Uncertainty of Overparametrized Neural Networks

ICML 2026

#p-ruegamer

SDR+26

Can Microcanonical Langevin Dynamics Leverage Mini-Batch Gradient Noise?

ICML 2026

#p-ruegamer

SDR+26a

Can Microcanonical Langevin Dynamics Leverage Mini-Batch Gradient Noise?

ISBA 2026

#p-ruegamer

KSK+26

On the Interplay of Priors and Overparametrization in Bayesian Neural Network Posteriors

AISTATS 2026

#p-ruegamer

SR26

Rethinking Intrinsic Dimension Estimation in Neural Representations

AISTATS 2026

#p-ruegamer

PBR26

Semi-Implicit Variational Inference via Kernelized Path Gradient Descent

AISTATS 2026

#p-bischl #p-ruegamer

SSM+26

Guiding Posterior Exploration With Optimizer-Derived Geometry

OPTIMAL @AISTATS 2026

#p-rueckert #p-ruegamer

SSD+26

Towards E-Value Based Stopping Rules for Bayesian Deep Ensembles

OPTIMAL @AISTATS 2026

#p-ruegamer

AAS+26

Bde: A Python Package for Bayesian Deep Ensembles via MILE

Preprint (May. 2026)

#p-ruegamer

DSK+26

On the Construction and Implications of Low-Loss Valleys in LoRA-Based Bayesian Inference

Preprint (May. 2026)

#p-ruegamer

Kol26

Advances in Deep Learning: Differentiable Sparsity, Overparameterization, and Semi-Structured Regression

Dissertation LMU München. Apr. 2026

#p-ruegamer

KMB+26

Smoothing the Edges: Smooth Optimization for Sparse Regularization Using Hadamard Overparametrization

Machine Learning 115.87. Apr. 2026

#p-bischl #p-mueller #p-ruegamer

XRW+26

Semantically Conditioned Diffusion Models for Cerebral DSA Synthesis

Preprint (Feb. 2026)

#p-bischl #p-ruegamer

XRB+26

Deep Generative Models in Digital Subtraction Angiography (DSA) and X-Ray Angiography: A Systematic Review

Artificial Intelligence Review 59.2. Jan. 2026

#p-bischl #p-ruegamer

KSK+25b

On the Interplay of Priors and Overparametrization in Bayesian Neural Network Posteriors

EIML @EurIPS 2025

#p-ruegamer

PSR+25a

Reliable Cell Trackers Say 'I Dunno!'

MedEurIPS @EurIPS 2025

#p-ruegamer

KFB+25

Differentiable Sparsity via D-Gating: Simple and Versatile Structured Penalization

NeurIPS 2025

#p-bischl #p-ruegamer

KRO25

Enhancing Heavy Rain Nowcasting With Multimodal Data: Integrating Radar and Satellite Observations

Preprint (Nov. 2025)

#p-ruegamer

PSR+25

How to Make Your Cell Tracker Say 'I Dunno!'

ICCV 2025

#p-ruegamer

LFZ+25

Semi-Automated LiDAR Vegetation Classification for Mediterranean Archaeology: Designing a Pipeline Leveraging a Multi-Layer Stacked Ensemble Approach

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-M-9-2025. Oct. 2025

#p-ruegamer

KRB+25

Achieving Interpretable Machine Learning by Functional Decomposition of Black-Box Models Into Explainable Predictor Effects

npj Artificial Intelligence 1.34. Oct. 2025

#p-ruegamer

KRS+25

On Training Survival Models With Scoring Rules

ECML-PKDD 2025

#p-bischl #p-ruegamer

OUF+25

Enhancing Traffic Accident Classifications: Application of NLP Methods for City Safety

ECML-PKDD 2025

#p-bischl #p-ruegamer

AKN+25

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

UAI 2025

#p-nagler #p-ruegamer

MRH+25

Position: The Future of Bayesian Prediction Is Prior-Fitted

ICML 2025

#p-ruegamer

PBR25

Revisiting Unbiased Implicit Variational Inference

ICML 2025

#p-bischl #p-ruegamer

RRF+25b

Can Transformers Learn Full Bayesian Inference in Context?

ICML 2025

#p-fortuin #p-ruegamer

SRN25

Adjustment for Confounding Using Pre-Trained Representations

ICML 2025

#p-nagler #p-ruegamer

SAS+25

An Interpretable Representation Learning Approach for Diffusion Tensor Imaging

MIDL 2025

#p-ruegamer

WIB+25

Preventing Sensitive Information Leakage via Post-Hoc Orthogonalization With Application to Chest Radiograph Embeddings

PAKDD 2025

#p-bischl #p-ingrisch #p-ruegamer

DKP+25

Paths and Ambient Spaces in Neural Loss Landscapes

AISTATS 2025

#p-nagler #p-ruegamer

SR25

Additive Model Boosting: New Insights and Path(ologie)s

AISTATS 2025

#p-ruegamer

KSK+25

Approximate Posteriors in Neural Networks: A Sampling Perspective

Workshop @AABI 2025

#p-ruegamer

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

RRF+25

Can Transformers Learn Full Bayesian Inference in Context?

FPI @ICLR 2025

#p-fortuin #p-ruegamer

RSB+25

Efficiently Warmstarting MCMC for BNNs

FPI @ICLR 2025

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

KSK+25a

Approximate Posteriors in Neural Networks: A Sampling Perspective

FPI @ICLR 2025

#p-ruegamer

KWB+25

Deep Weight Factorization: Sparse Learning Through the Lens of Artificial Symmetries

ICLR 2025

#p-bischl #p-ruegamer

LRB+25

Calibrating LLMs With Information-Theoretic Evidential Deep Learning

ICLR 2025

#p-bischl #p-ruegamer

SRN+25

Microcanonical Langevin Ensembles: Advancing the Sampling of Bayesian Neural Networks

ICLR 2025

#p-ruegamer

KBR25

Differentiable Attention Sparsity via Structured D-Gating

SLLM @ICLR 2025

#p-bischl #p-ruegamer

RRF+25a

Can Transformers Learn Full Bayesian Inference in Context?

SynthData @ICLR 2025

#p-fortuin #p-ruegamer

SKR+25

Machine Learning-Based Forecasting of Daily Acute Ischemic Stroke Admissions Using Weather Data

npj Digital Medicine 8.225. Apr. 2025

#p-bischl #p-ruegamer

WDR+25

Post-Training Network Compression for 3D Medical Image Segmentation: Reducing Computational Efforts via Tucker Decomposition

Radiology: Artificial Intelligence 7.2. Jan. 2025

#p-bischl #p-ingrisch #p-ruegamer

RLA+24

A Functional Extension of Semi-Structured Networks

NeurIPS 2024

#p-ruegamer

KBD+24

Estimating Conditional Distributions With Neural Networks Using R Package Deeptrafo

Journal of Statistical Software 111.10. Dec. 2024

#p-ruegamer

GRL+24

Functional Data Analysis: An Introduction and Recent Developments

Biometrical Journal 66.7. Oct. 2024

#p-ruegamer

WWP+24

Towards Efficient Posterior Sampling in Deep Neural Networks via Symmetry Removal (Extended Abstract)

IJCAI 2024

#p-bischl #p-guennemann #p-ruegamer

OHR+24

Fusing Structure From Motion and Simulation-Augmented Pose Regression From Optical Flow for Challenging Indoor Environments

Journal of Visual Communication and Image Representation 103. Aug. 2024

#p-bischl #p-ruegamer

BLP+24

Motion Analysis in Neurological Rehabilitation: From the Lab to the Clinic

Translational Neurorehabilitation Chapter 7. Aug. 2024

#p-ruegamer

HLE+24

Position: Why We Must Rethink Empirical Research in Machine Learning

ICML 2024

#p-bischl #p-boulesteix #p-feurer #p-huellermeier #p-ruegamer

PSP+24

Position: Bayesian Deep Learning Is Needed in the Age of Large-Scale AI

ICML 2024

#p-fortuin #p-ruegamer

RKW+24

Generalizing Orthogonalization for Models With Non-Linearities

ICML 2024

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

SWP+24

Connecting the Dots: Is Mode Connectedness the Key to Feasible Sample-Based Inference in Bayesian Neural Networks?

ICML 2024

#p-bischl #p-ruegamer

RKC+24

Interpretable Machine Learning for TabPFN

XAI 2024

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

KKS+24

How Inverse Conditional Flows Can Serve as a Substitute for Distributional Regression

UAI 2024

#p-bischl #p-ruegamer

KRS24

Achieving Interpretable Machine Learning by Functional Decomposition of Black-Box Models Into Explainable Predictor Effects

Preprint (Jul. 2024)

#p-ruegamer

CBR+24

Leveraging (Sentence) Transformer Models With Contrastive Learning for Identifying Machine-Generated Text

SemEval @NAACL 2024

#p-ruegamer #p-schuetze

RPB+24

Mixture of Experts Distributional Regression: Implementation Using Robust Estimation With Adaptive First-Order Methods

Advances in Statistical Analysis 108. Jun. 2024

#p-bischl #p-ruegamer

SR24

Editorial Special Issue: Bridging the Gap Between AI and Statistics

Advances in Statistical Analysis 108. Jun. 2024

#p-ruegamer

DRS+24

Bayesian Semi-Structured Subspace Inference

AISTATS 2024

#p-ruegamer

Rue24

Scalable Higher-Order Tensor Product Spline Models

AISTATS 2024

#p-ruegamer

TRK+24

Interpretable Additive Tabular Transformer Networks

Transactions on Machine Learning Research Vol. 2024. May. 2024

#p-ruegamer

LPR+24

Strategies to Optimise Machine Learning Classification Performance When Using Biomechanical Features

Journal of Biomechanics 165. Mar. 2024

#p-bischl #p-ruegamer

GRG24

Methoden Für Die Analyse Funktionaler Daten

Moderne Verfahren Der Angewandten Statistik Living Reference Work Entry. Mar. 2024

#p-ruegamer

LRB24

Neuromechanical Stabilisation of the Centre of Mass During Running

Gait and Posture 108. Feb. 2024

#p-ruegamer

SBR24

Privacy-Preserving and Lossless Distributed Estimation of High-Dimensional Generalized Additive Mixed Models

Statistics and Computing 34.1. Feb. 2024

#p-bischl #p-ruegamer

WIB+24

Constrained Probabilistic Mask Learning for Task-Specific Undersampled MRI Reconstruction

WACV 2024

#p-bischl #p-ingrisch #p-ruegamer

ZYM+23a

Baby’s CoThought: Leveraging Large Language Models for Enhanced Reasoning in Compact Models

BabyLM Challenge @CoNLL 2023)

#p-kasneci-gjergji #p-kreuter #p-ruegamer #p-schuetze

SCS+23

A Comprehensive Machine Learning Benchmark Study for Radiomics-Based Survival Analysis of CT Imaging Data in Patients With Hepatic Metastases of CRC

Investigative Radiology 58.12. Dec. 2023

#p-bischl #p-ingrisch #p-ruegamer

WIB+23a

Post-Hoc Orthogonalization for Mitigation of Protected Feature Bias in CXR Embeddings

Preprint (Nov. 2023)

#p-bischl #p-ingrisch #p-ruegamer

WWP+23

Towards Efficient MCMC Sampling in Bayesian Neural Networks by Exploiting Symmetry

ECML-PKDD 2023

#p-bischl #p-guennemann #p-ruegamer

LKR+23

Automatic Variable Selection Algorithms in Prognostic Factor Research in Neck Pain

Journal of Clinical Medicine 12.19. Sep. 2023

#p-ruegamer

ORH+23

IEEE Access 11. Aug. 2023

#p-bischl #p-ruegamer

Rue23

A New PHO-Rmula for Improved Performance of Semi-Structured Networks

ICML 2023

#p-ruegamer

KBM+23

Sparse Modality Regression

IWSM 2023

#p-bischl #p-mueller #p-ruegamer

LRM+23

Smooth and Accurate Predictions of Joint Contact Force Timeseries in Gait Using Overparameterised Deep Neural Networks

Frontiers in Bioengineering and Biotechnology 11. Jul. 2023

#p-ruegamer

KMB+23a

Smoothing the Edges: Smooth Optimization for Sparse Regularization Using Hadamard Overparametrization

Preprint (Jul. 2023)

#p-bischl #p-mueller #p-ruegamer

WIB+23

Cascaded Latent Diffusion Models for High-Resolution Chest X-Ray Synthesis

PAKDD 2023

#p-bischl #p-ingrisch #p-ruegamer

RRB+23

Dependent State Space Student-T Processes for Imputation and Data Augmentation in Plasma Diagnostics

Contributions to Plasma Physics 63.5-6. May. 2023

#p-bischl #p-ruegamer

PBR23

Approximate Bayesian Inference With Stein Functional Variational Gradient Descent

ICLR 2023

#p-bischl #p-ruegamer

DSB+23

Frequentist Uncertainty Quantification in Semi-Structured Neural Networks

AISTATS 2023

#p-bischl #p-ruegamer

SBR23

Accelerated Componentwise Gradient Boosting Using Efficient Data Representation and Momentum-Based Optimization

Journal of Computational and Graphical Statistics 32.2. Apr. 2023

#p-bischl #p-ruegamer

RKK23

Semi-Structured Distributional Regression

American Statistician 78.1. Feb. 2023

#p-ruegamer

RBK+23

Probabilistic Time Series Forecasts With Autoregressive Transformation Models

Statistics and Computing 33.2. Feb. 2023

#p-ruegamer

Rue23a

Mixdistreg: An R Package for Fitting Mixture of Experts Distributional Regression With Adaptive First-Order Methods

Preprint (Feb. 2023)

#p-ruegamer

ORH+22c

Benchmarking Online Sequence-to-Sequence and Character-Based Handwriting Recognition From IMU-Enhanced Pens

International Journal on Document Analysis and Recognition 25.4. Dec. 2022

#p-bischl #p-ruegamer

FDG+22

Challenges in Interpreting Epidemiological Surveillance Data – Experiences From Germany

Journal of Computational and Graphical Statistics 32.3. Dec. 2022

#p-bischl #p-kauermann #p-kuechenhoff #p-ruegamer

RDR+22

Joint Debiased Representation Learning and Imbalanced Data Clustering

Workshop @ICDM 2022

#p-bischl #p-ruegamer

ZMN+22

What Cleaves? Is Proteasomal Cleavage Prediction Reaching a Ceiling?

LMRL @NeurIPS 2022

#p-bischl #p-kreuter #p-ruegamer #p-schuetze

ORH+22a

Domain Adaptation for Time-Series Classification to Mitigate Covariate Shift

MM 2022

#p-bischl #p-ruegamer

RRB+22

Data Augmentation for Disruption Prediction via Robust Surrogate Models

Journal of Plasma Physics 88.5. Oct. 2022

#p-bischl #p-ruegamer

RBW+22a

Factorized Structured Regression for Large-Scale Varying Coefficient Models

ECML-PKDD 2022

#p-bischl #p-mueller #p-ruegamer

BSC+22

Developing Open Source Educational Resources for Machine Learning and Data Science

Teaching Machine Learning and Artificial Intelligence Workshop @ECML-PKDD 2022

#p-bischl #p-ruegamer #p-scheipl

WIB+22

Implicit Embeddings via GAN Inversion for High Resolution Chest Radiographs

MAD @MICCAI 2022

#p-bischl #p-ingrisch #p-ruegamer

ORH+22e

Representation Learning for Tablet and Paper Domain Adaptation in Favor of Online Handwriting Recognition

MPRSS @ICPR 2022

#p-bischl #p-ruegamer

ORR+22

Benchmarking Visual-Inertial Deep Multimodal Fusion for Relative Pose Regression and Odometry-Aided Absolute Pose Regression

Preprint (Aug. 2022)

#p-bischl #p-ruegamer

KLL+22

Uncertainty-Aware Evaluation of Time-Series Classification for Online Handwriting Recognition With Domain Shift

STRL 2022 @IJCAI-ECAI 2022

#p-bischl #p-ruegamer

MWR+22

A Deep Learning Based Classification of Atmospheric Circulation Types Over Europe: Projection of Future Changes in a CMIP6 Large Ensemble

Environmental Research Letters 17.8. Jul. 2022

#p-kuechenhoff #p-ruegamer

KWB+22

DeepPAMM: Deep Piecewise Exponential Additive Mixed Models for Complex Hazard Structures in Survival Analysis

PAKDD 2022

#p-bischl #p-ruegamer

Rue22

Additive Higher-Order Factorization Machines

Preprint (May. 2022)

#p-ruegamer

FDR22

Combining Graph Neural Networks and Spatio-Temporal Disease Models to Predict COVID-19 Cases in Germany

Scientific Reports 12.3930. Mar. 2022

#p-bischl #p-kauermann #p-ruegamer

ORH+22

Preprint (Mar. 2022)

#p-bischl #p-ruegamer

ORH+22b

Joint Classification and Trajectory Regression of Online Handwriting Using a Multi-Task Learning Approach

WACV 2022

#p-bischl #p-ruegamer

WIF+21

Survival-Oriented Embeddings for Improving Accessibility to Complex Data Structures

Bridging the Gap: From ML Research to Clinical Practice @NeurIPS 2021

#p-bischl #p-ingrisch #p-ruegamer

WIB+21

Towards Modelling Hazard Factors in Unstructured Data Spaces Using Gradient-Based Latent Interpolation

Deep Generative Models and Downstream Applications @NeurIPS 2021

#p-bischl #p-ingrisch #p-ruegamer

MWR21

Identifying the Atmospheric Drivers of Drought and Heat Using a Smoothed Deep Learning Approach

Tackling Climate Change With ML @NeurIPS 2021

#p-kuechenhoff #p-ruegamer

CSB+21

Automatic Componentwise Boosting: An Interpretable AutoML System

ADS @ECML-PKDD 2021

#p-bischl #p-ruegamer

BHR21

Deep Conditional Transformation Models

ECML-PKDD 2021

#p-ruegamer

KPW+21

Semi-Structured Deep Piecewise Exponential Models

AAAI-SPACA 2021

#p-bischl #p-ruegamer #p-wachinger

GHR+21

Deep Semi-Supervised Learning for Time Series Classification

Preprint (Feb. 2021)

#p-bischl #p-ruegamer

RSB+21a

Deepregression: Fitting Semi-Structured Deep Distributional Regression in R

2021

#p-bischl #p-ruegamer

RPB20

Neural Mixture Distributional Regression

Preprint (Oct. 2020)

#p-bischl #p-ruegamer

BRS+20

A General Machine Learning Framework for Survival Analysis

ECML-PKDD 2020

#p-bischl #p-ruegamer #p-scheipl

2018-12-10 - Last modified: 2018-12-10

#p-ruegamer

Higher-Order Hit-&-Run Samplers for Linearly Constrained Densities

Position: The Time for Sampling Is Now! Charting a New Course for Bayesian Deep Learning

On the Epistemic Uncertainty of Overparametrized Neural Networks

Can Microcanonical Langevin Dynamics Leverage Mini-Batch Gradient Noise?

Can Microcanonical Langevin Dynamics Leverage Mini-Batch Gradient Noise?

On the Interplay of Priors and Overparametrization in Bayesian Neural Network Posteriors

Rethinking Intrinsic Dimension Estimation in Neural Representations

Semi-Implicit Variational Inference via Kernelized Path Gradient Descent

Guiding Posterior Exploration With Optimizer-Derived Geometry

Towards E-Value Based Stopping Rules for Bayesian Deep Ensembles

Bde: A Python Package for Bayesian Deep Ensembles via MILE

On the Construction and Implications of Low-Loss Valleys in LoRA-Based Bayesian Inference

Advances in Deep Learning: Differentiable Sparsity, Overparameterization, and Semi-Structured Regression

Smoothing the Edges: Smooth Optimization for Sparse Regularization Using Hadamard Overparametrization

Semantically Conditioned Diffusion Models for Cerebral DSA Synthesis

Deep Generative Models in Digital Subtraction Angiography (DSA) and X-Ray Angiography: A Systematic Review

On the Interplay of Priors and Overparametrization in Bayesian Neural Network Posteriors

Reliable Cell Trackers Say 'I Dunno!'

Differentiable Sparsity via D-Gating: Simple and Versatile Structured Penalization

Enhancing Heavy Rain Nowcasting With Multimodal Data: Integrating Radar and Satellite Observations

How to Make Your Cell Tracker Say 'I Dunno!'

Semi-Automated LiDAR Vegetation Classification for Mediterranean Archaeology: Designing a Pipeline Leveraging a Multi-Layer Stacked Ensemble Approach

Achieving Interpretable Machine Learning by Functional Decomposition of Black-Box Models Into Explainable Predictor Effects

On Training Survival Models With Scoring Rules

Enhancing Traffic Accident Classifications: Application of NLP Methods for City Safety

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

Position: The Future of Bayesian Prediction Is Prior-Fitted

Revisiting Unbiased Implicit Variational Inference

Can Transformers Learn Full Bayesian Inference in Context?

Adjustment for Confounding Using Pre-Trained Representations

An Interpretable Representation Learning Approach for Diffusion Tensor Imaging

Preventing Sensitive Information Leakage via Post-Hoc Orthogonalization With Application to Chest Radiograph Embeddings

Paths and Ambient Spaces in Neural Loss Landscapes

Additive Model Boosting: New Insights and Path(ologie)s

Approximate Posteriors in Neural Networks: A Sampling Perspective

Uncertainty Quantification for Prior-Fitted Networks Using Martingale Posteriors

Uncertainty Quantification for Prior-Fitted Networks Using Martingale Posteriors

Can Transformers Learn Full Bayesian Inference in Context?

Efficiently Warmstarting MCMC for BNNs

Approximate Posteriors in Neural Networks: A Sampling Perspective

Deep Weight Factorization: Sparse Learning Through the Lens of Artificial Symmetries

Calibrating LLMs With Information-Theoretic Evidential Deep Learning

Microcanonical Langevin Ensembles: Advancing the Sampling of Bayesian Neural Networks

Differentiable Attention Sparsity via Structured D-Gating

Can Transformers Learn Full Bayesian Inference in Context?

Machine Learning-Based Forecasting of Daily Acute Ischemic Stroke Admissions Using Weather Data

Post-Training Network Compression for 3D Medical Image Segmentation: Reducing Computational Efforts via Tucker Decomposition

A Functional Extension of Semi-Structured Networks

Estimating Conditional Distributions With Neural Networks Using R Package Deeptrafo

Functional Data Analysis: An Introduction and Recent Developments

Towards Efficient Posterior Sampling in Deep Neural Networks via Symmetry Removal (Extended Abstract)

Fusing Structure From Motion and Simulation-Augmented Pose Regression From Optical Flow for Challenging Indoor Environments

Motion Analysis in Neurological Rehabilitation: From the Lab to the Clinic

Position: Why We Must Rethink Empirical Research in Machine Learning

Position: Bayesian Deep Learning Is Needed in the Age of Large-Scale AI

Generalizing Orthogonalization for Models With Non-Linearities

Connecting the Dots: Is Mode Connectedness the Key to Feasible Sample-Based Inference in Bayesian Neural Networks?

Interpretable Machine Learning for TabPFN

How Inverse Conditional Flows Can Serve as a Substitute for Distributional Regression

Achieving Interpretable Machine Learning by Functional Decomposition of Black-Box Models Into Explainable Predictor Effects

Leveraging (Sentence) Transformer Models With Contrastive Learning for Identifying Machine-Generated Text

Mixture of Experts Distributional Regression: Implementation Using Robust Estimation With Adaptive First-Order Methods

Editorial Special Issue: Bridging the Gap Between AI and Statistics

Bayesian Semi-Structured Subspace Inference

Scalable Higher-Order Tensor Product Spline Models

Interpretable Additive Tabular Transformer Networks

Strategies to Optimise Machine Learning Classification Performance When Using Biomechanical Features

Methoden Für Die Analyse Funktionaler Daten

Neuromechanical Stabilisation of the Centre of Mass During Running

Privacy-Preserving and Lossless Distributed Estimation of High-Dimensional Generalized Additive Mixed Models

Constrained Probabilistic Mask Learning for Task-Specific Undersampled MRI Reconstruction

Baby’s CoThought: Leveraging Large Language Models for Enhanced Reasoning in Compact Models

A Comprehensive Machine Learning Benchmark Study for Radiomics-Based Survival Analysis of CT Imaging Data in Patients With Hepatic Metastases of CRC

Post-Hoc Orthogonalization for Mitigation of Protected Feature Bias in CXR Embeddings

Towards Efficient MCMC Sampling in Bayesian Neural Networks by Exploiting Symmetry

Automatic Variable Selection Algorithms in Prognostic Factor Research in Neck Pain

Auxiliary Cross-Modal Representation Learning With Triplet Loss Functions for Online Handwriting Recognition

A New PHO-Rmula for Improved Performance of Semi-Structured Networks

Sparse Modality Regression