Integral Imprecise Probability Metrics

22 May 2025

Papers citing "Integral Imprecise Probability Metrics"

50 / 52 papers shown

Title
Position: Epistemic Artificial Intelligence is Essential for Machine Learning Models to Know When They Do Not Know Shireen Kudukkil Manchingal Fabio Cuzzolin 87 1 0 08 May 2025
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 90 3 0 25 Apr 2025
Random-Set Large Language Models Muhammad Mubashar Shireen Kudukkil Manchingal Fabio Cuzzolin 91 1 0 25 Apr 2025
Truthful Elicitation of Imprecise Forecasts Anurag Singh Siu Lun Chau Krikamol Muandet 103 1 0 20 Mar 2025
A calibration test for evaluating set-based epistemic uncertainty representations Mira Jürgens Thomas Mortier Eyke Hüllermeier Viktor Bengs Willem Waegeman 63 1 0 22 Feb 2025
Conformal Prediction Regions are Imprecise Highest Density Regions Michele Caprio Yusuf Sale Eyke Hüllermeier 122 1 0 10 Feb 2025
CreINNs: Credal-Set Interval Neural Networks for Uncertainty Estimation in Classification Tasks Kaizheng Wang Keivan K1 Shariatmadar Shireen Kudukkil Manchingal Fabio Cuzzolin David Moens Hans Hallez UQCV BDL 175 13 0 28 Jan 2025
Rethinking Aleatoric and Epistemic Uncertainty Freddie Bickford-Smith Jannik Kossen Eleanor Trollope Mark van der Wilk Adam Foster Tom Rainforth UD PER 51 5 0 31 Dec 2024
Conformalized Credal Regions for Classification with Ambiguous Ground Truth Michele Caprio David Stutz Shuo Li Arnaud Doucet UQCV 142 5 0 07 Nov 2024
An Overview of Causal Inference using Kernel Embeddings Dino Sejdinovic CML BDL 84 4 0 30 Oct 2024
Robust Kernel Hypothesis Testing under Data Corruption Antonin Schrab Ilmun Kim 70 4 0 30 May 2024
Domain Generalisation via Imprecise Learning Anurag Singh Siu Lun Chau S. Bouabid Krikamol Muandet AI4CE OOD 66 9 0 06 Apr 2024
Hierarchical Integral Probability Metrics: A distance on random probability measures with low sample complexity Marta Catalano Hugo Lavenant 37 3 0 01 Feb 2024
Second-Order Uncertainty Quantification: Variance-Based Measures Yusuf Sale Paul Hofman Lisa Wimmer Eyke Hüllermeier Thomas Nagler PER UQCV UD 51 11 0 30 Dec 2023
Second-Order Uncertainty Quantification: A Distance-Based Approach Yusuf Sale Viktor Bengs Michele Caprio Eyke Hüllermeier PER UQCV UD 48 23 0 02 Dec 2023
A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions Lei Huang Weijiang Yu Weitao Ma Weihong Zhong Zhangyin Feng ... Qianglong Chen Weihua Peng Xiaocheng Feng Bing Qin Ting Liu LRM HILM 78 805 0 09 Nov 2023
Distributionally Robust Statistical Verification with Imprecise Neural Networks Souradeep Dutta Michele Caprio Vivian Lin Matthew Cleaveland Kuk Jin Jang I. Ruchkin O. Sokolsky Insup Lee OOD AAML 138 8 0 28 Aug 2023
Approximating Counterfactual Bounds while Fusing Observational, Biased and Randomised Data Sources Marco Zaffalon Alessandro Antonucci Rafael Cabañas David Huber 44 6 0 31 Jul 2023
Conformal prediction under ambiguous ground truth David Stutz Abhijit Guha Roy Tatiana Matejovicova Patricia Strachan A. Cemgil Arnaud Doucet 123 18 0 18 Jul 2023
A Novel Bayes' Theorem for Upper Probabilities Michele Caprio Yusuf Sale Eyke Hüllermeier Insup Lee 46 12 0 13 Jul 2023
Is the Volume of a Credal Set a Good Measure for Epistemic Uncertainty? Yusuf Sale Michele Caprio Eyke Hüllermeier UD 39 27 0 16 Jun 2023
Explaining the Uncertain: Stochastic Shapley Values for Gaussian Process Models Siu Lun Chau Krikamol Muandet Dino Sejdinovic FAtt 77 15 0 24 May 2023
Constriction for sets of probabilities Michele Caprio Teddy Seidenfeld 32 8 0 13 Jan 2023
ROAD-R: The Autonomous Driving Dataset with Logical Requirements Eleonora Giunchiglia Mihaela C. Stoian Salman Khan Fabio Cuzzolin Thomas Lukasiewicz AI4TS 83 34 0 04 Oct 2022
Quantifying Aleatoric and Epistemic Uncertainty in Machine Learning: Are Conditional Entropy and Mutual Information Appropriate Measures? Lisa Wimmer Yusuf Sale Paul Hofman Bern Bischl Eyke Hüllermeier PER UD 60 74 0 07 Sep 2022
Gated Domain Units for Multi-source Domain Generalization Simon Foll Alina Dubatovka Eugen Ernst Siu Lun Chau Martin Maritsch Patrik Okanovic Gudrun Thater J. M. Buhmann Felix Wortmann Krikamol Muandet OOD 95 4 0 24 Jun 2022
RKHS-SHAP: Shapley Values for Kernel Methods Siu Lun Chau Robert Hu Javier I. González Dino Sejdinovic FAtt 38 20 0 18 Oct 2021
Dynamic Precise and Imprecise Probability Kinematics Michele Caprio Ruobin Gong 16 10 0 08 Oct 2021
Ensemble-based Uncertainty Quantification: Bayesian versus Credal Inference M. Shaker Eyke Hüllermeier UD UQCV PER BDL 262 17 0 21 Jul 2021
An Imprecise SHAP as a Tool for Explaining the Class Probability Distributions under Limited Training Data Lev V. Utkin A. Konstantinov Kirill Vishniakov FAtt 59 6 0 16 Jun 2021
BayesIMP: Uncertainty Quantification for Causal Data Fusion Siu Lun Chau Jean-François Ton Javier I. González Yee Whye Teh Dino Sejdinovic CML 35 20 0 07 Jun 2021
Deconditional Downscaling with Gaussian Processes Siu Lun Chau S. Bouabid Dino Sejdinovic BDL 42 22 0 27 May 2021
Ergodic Theorems for Dynamic Imprecise Probability Kinematics Michele Caprio S. Mukherjee 18 9 0 13 Mar 2020
Aleatoric and Epistemic Uncertainty with Random Forests M. Shaker Eyke Hüllermeier BDL UD PER 34 71 0 03 Jan 2020
Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods Eyke Hüllermeier Willem Waegeman PER UD 163 1,388 0 21 Oct 2019
MMD-Bayes: Robust Bayesian Estimation via Maximum Mean Discrepancy Badr-Eddine Chérief-Abdellatif Pierre Alquier 117 74 0 29 Sep 2019
Statistical Inference for Generative Models with Maximum Mean Discrepancy François‐Xavier Briol Alessandro Barp Andrew B. Duncan Mark Girolami 44 72 0 13 Jun 2019
Maximum Mean Discrepancy Gradient Flow Michael Arbel Anna Korba Adil Salim Arthur Gretton 83 163 0 11 Jun 2019
Evidential Deep Learning to Quantify Classification Uncertainty Murat Sensoy Lance M. Kaplan M. Kandemir OOD UQCV EDL BDL 134 969 0 05 Jun 2018
Counterfactual Mean Embeddings Krikamol Muandet Motonobu Kanagawa Sorawit Saengkyongam S. Marukatat CML OffRL 44 39 0 22 May 2018
MMD GAN: Towards Deeper Understanding of Moment Matching Network Chun-Liang Li Wei-Cheng Chang Yu Cheng Yiming Yang Barnabás Póczós GAN 53 720 0 24 May 2017
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? Alex Kendall Y. Gal BDL OOD UD UQCV PER 286 4,667 0 15 Mar 2017
Uncertain programming model for multi-item solid transportation problem Hasan Dalman 66 732 0 31 May 2016
Learning Theory for Distribution Regression Z. Szabó Bharath K. Sriperumbudur Barnabás Póczós Arthur Gretton OOD 35 138 0 08 Nov 2014
Credal Model Averaging for classification: representing prior ignorance and expert opinions Giorgio Corani A. Mignatti 33 11 0 14 May 2014
On the optimal estimation of probability measures in weak and strong topologies Bharath K. Sriperumbudur OT 81 65 0 30 Oct 2013
Domain Generalization via Invariant Feature Representation Krikamol Muandet David Balduzzi Bernhard Schölkopf OOD 87 1,166 0 10 Jan 2013
Multiple Source Adaptation and the Renyi Divergence Yishay Mansour M. Mohri Afshin Rostamizadeh 70 148 0 09 May 2012
Learning from Distributions via Support Measure Machines Krikamol Muandet Kenji Fukumizu Francesco Dinuzzo Bernhard Schölkopf 82 197 0 29 Feb 2012
Universality, Characteristic Kernels and RKHS Embedding of Measures Bharath K. Sriperumbudur Kenji Fukumizu Gert R. G. Lanckriet 157 526 0 03 Mar 2010