:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Melev, Ivan, Kauermann, Goeran
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2506.03670
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Structure Is Not Enough: Leveraging Behavior for Neural Network Weight Reconstruction
by: Meynent, Léo, et al.
Published: (2025)

Sources of Uncertainty in Supervised Machine Learning -- A Statisticians' View
by: Gruber, Cornelia, et al.
Published: (2023)

Uncertainty Quantification and Propagation in Surrogate-based Bayesian Inference
by: Reiser, Philipp, et al.
Published: (2023)

NeuralSurv: Deep Survival Analysis with Bayesian Uncertainty Quantification
by: Monod, Mélodie, et al.
Published: (2025)

Multivariate Bayesian Last Layer for Regression with Uncertainty Quantification and Decomposition
by: Wang, Han, et al.
Published: (2024)

Self-Supervised Laplace Approximation for Bayesian Uncertainty Quantification
by: Rodemann, Julian, et al.
Published: (2026)

Bayesian Parametric Matrix Models: Principled Uncertainty Quantification for Spectral Learning
by: Nooraiepour, Mohammad
Published: (2025)

Uncertainty Quantification With Noise Injection in Neural Networks: A Bayesian Perspective
by: Yuan, Xueqiong, et al.
Published: (2025)

Quantile-Free Uncertainty Quantification in Graph Neural Networks
by: park, Soyoung, et al.
Published: (2026)

Bayesian Uncertainty Quantification with Anchored Ensembles for Robust EV Power Consumption Prediction
by: Farhani, Ghazal, et al.
Published: (2025)

Uncertainty Quantification of Large Language Models using Approximate Bayesian Computation
by: Sharma, Mridul, et al.
Published: (2025)

Uncertainty Quantification in PINNs for Turbulent Flows: Bayesian Inference and Repulsive Ensembles
by: Shukla, Khemraj, et al.
Published: (2026)

Fully Bayesian Spectral Clustering and Benchmarking with Uncertainty Quantification for Small Area Estimation
by: Fúquene-Patiño, Jairo
Published: (2025)

Conformalized Generative Bayesian Imaging: An Uncertainty Quantification Framework for Computational Imaging
by: Ekmekci, Canberk, et al.
Published: (2025)

Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents
by: Kirchhof, Michael, et al.
Published: (2025)

Human-in-the-loop: Towards Label Embeddings for Measuring Classification Difficulty
by: Hechinger, Katharina, et al.
Published: (2023)

Uncertainty Quantification of Data-Driven Output Predictors in the Output Error Setting
by: Kaviani, Farzan, et al.
Published: (2024)

Epistemic Wrapping for Uncertainty Quantification
by: Sultana, Maryam, et al.
Published: (2025)

Offline Bayesian Aleatoric and Epistemic Uncertainty Quantification and Posterior Value Optimisation in Finite-State MDPs
by: Valdettaro, Filippo, et al.
Published: (2024)

Uncertainty Quantification with Bayesian Higher Order ReLU KANs
by: Giroux, James, et al.
Published: (2024)

Dynamical System Identification, Model Selection and Model Uncertainty Quantification by Bayesian Inference
by: Niven, Robert K., et al.
Published: (2024)

Uncertainty Quantification With Multiple Sources
by: Ying, Mufang, et al.
Published: (2024)

Understanding the Trade-offs in Accuracy and Uncertainty Quantification: Architecture and Inference Choices in Bayesian Neural Networks
by: Sheinkman, Alisa, et al.
Published: (2025)

Functional PCA and Deep Neural Networks-based Bayesian Inverse Uncertainty Quantification with Transient Experimental Data
by: Xie, Ziyu, et al.
Published: (2023)

Multi-Fidelity Bayesian Neural Network for Uncertainty Quantification in Transonic Aerodynamic Loads
by: Vaiuso, Andrea, et al.
Published: (2024)

Is the Last Layer Sufficient for Uncertainty Quantification?
by: Wilson, Joseph, et al.
Published: (2026)

Uncertainty Quantification in the Tsetlin Machine
by: Helin, Runar, et al.
Published: (2025)

Uncertainty Quantification in SVM prediction
by: Anand, Pritam
Published: (2025)

Uncertainty Quantification for Quantum Computing
by: Bennink, Ryan, et al.
Published: (2026)

Uncertainty Quantification in Multivariable Regression for Material Property Prediction with Bayesian Neural Networks
by: Li, Longze, et al.
Published: (2023)

Distribution-Free Uncertainty Quantification in Mechanical Ventilation Treatment: A Conformal Deep Q-Learning Framework
by: Eghbali, Niloufar, et al.
Published: (2024)

Bayesian Quantification with Black-Box Estimators
by: Ziegler, Albert, et al.
Published: (2023)

Uncertainty Quantification Metrics for Deep Regression
by: Lind, Simon Kristoffersson, et al.
Published: (2024)

Interventional Processes for Causal Uncertainty Quantification
by: Dance, Hugh, et al.
Published: (2024)

Multidimensional Uncertainty Quantification via Optimal Transport
by: Kotelevskii, Nikita, et al.
Published: (2025)

Uncertainty Quantification with the Empirical Neural Tangent Kernel
by: Wilson, Joseph, et al.
Published: (2025)

Multivariate Uncertainty Quantification with Tomographic Quantile Forests
by: Kanazawa, Takuya
Published: (2025)

Linear Opinion Pooling for Uncertainty Quantification on Graphs
by: Damke, Clemens, et al.
Published: (2024)

Label-wise Aleatoric and Epistemic Uncertainty Quantification
by: Sale, Yusuf, et al.
Published: (2024)

Activation-Space Uncertainty Quantification for Pretrained Networks
by: Bergna, Richard, et al.
Published: (2026)