Second-Order Uncertainty Quantification: A Distance-Based Approach

Second-Order Uncertainty Quantification: A Distance-Based Approach

2 December 2023

Eyke Hüllermeier

Papers citing "Second-Order Uncertainty Quantification: A Distance-Based Approach"

18 / 18 papers shown

Title
An Axiomatic Assessment of Entropy- and Variance-based Uncertainty Quantification in Regression Christopher Bülte Yusuf Sale Timo Löhr Paul Hofman Gitta Kutyniok Eyke Hüllermeier UD 70 0 0 25 Apr 2025
Prior2Former -- Evidential Modeling of Mask Transformers for Assumption-Free Open-World Panoptic Segmentation Sebastian Schmidt Julius Körner Dominik Fuchsgruber Stefano Gasperini F. Tombari Stephan Günnemann 26 0 0 07 Apr 2025
Conformal Prediction Regions are Imprecise Highest Density Regions Michele Caprio Yusuf Sale Eyke Hüllermeier 67 0 0 10 Feb 2025
Confidence Elicitation: A New Attack Vector for Large Language Models Brian Formento Chuan-Sheng Foo See-Kiong Ng AAML 101 0 0 07 Feb 2025
Conformalized Credal Regions for Classification with Ambiguous Ground Truth Michele Caprio David Stutz Shuo Li Arnaud Doucet UQCV 78 4 0 07 Nov 2024
Probabilistic Degeneracy Detection for Point-to-Plane Error Minimization Johan Hatleskog Kostas Alexis 3DPC 47 2 0 14 Oct 2024
Enhancing Uncertainty Quantification in Drug Discovery with Censored Regression Labels Emma Svensson Hannah Rosa Friesacher S. Winiwarter Lewis H. Mervin Adam Arany Ola Engkvist 50 2 0 06 Sep 2024
Label-wise Aleatoric and Epistemic Uncertainty Quantification Yusuf Sale Paul Hofman Timo Löhr Lisa Wimmer Thomas Nagler Eyke Hüllermeier PER UD UQCV 53 7 0 04 Jun 2024
Scalable Bayesian Learning with posteriors Samuel Duffield Kaelan Donatella Johnathan Chiu Phoebe Klett Daniel Simpson BDL UQCV 65 1 0 31 May 2024
Conformal Predictions for Probabilistically Robust Scalable Machine Learning Classification Alberto Carlevaro Teodoro Alamo Fabrizio Dabbene Maurizio Mongelli 28 2 0 15 Mar 2024
Generalising realisability in statistical learning theory under epistemic uncertainty Fabio Cuzzolin CML 40 0 0 22 Feb 2024
Predictive Uncertainty Quantification via Risk Decompositions for Strictly Proper Scoring Rules Nikita Kotelevskii Maxim Panov PER UQCV UD 37 5 0 16 Feb 2024
Is Epistemic Uncertainty Faithfully Represented by Evidential Deep Learning Methods? Mira Jürgens Nis Meinert Viktor Bengs Eyke Hüllermeier Willem Waegeman UQCV UD PER EDL BDL 34 11 0 14 Feb 2024
Credal Learning Theory Michele Caprio Maryam Sultana Eleni Elia Fabio Cuzzolin FedML 48 11 0 01 Feb 2024
Second-Order Uncertainty Quantification: Variance-Based Measures Yusuf Sale Paul Hofman Lisa Wimmer Eyke Hüllermeier Thomas Nagler PER UQCV UD 37 8 0 30 Dec 2023
On Second-Order Scoring Rules for Epistemic Uncertainty Quantification Viktor Bengs Eyke Hüllermeier Willem Waegeman UQCV 218 25 0 30 Jan 2023
The Unreasonable Effectiveness of Deep Evidential Regression N. Meinert J. Gawlikowski Alexander Lavin UQCV EDL 192 35 0 20 May 2022
Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation Dennis Ulmer Christian Hardmeier J. Frellsen BDL UQCV UD EDL PER 55 48 0 06 Oct 2021