Quantification of Uncertainty with Adversarial Models

Quantification of Uncertainty with Adversarial Models

6 July 2023

Kajetan Schweighofer

Mykyta Ielanskyi

Sepp Hochreiter

Papers citing "Quantification of Uncertainty with Adversarial Models"

18 / 18 papers shown

Title
Feature Fitted Online Conformal Prediction for Deep Time Series Forecasting Model Xiannan Huang Shuhan Qiu AI4TS 14 0 0 13 May 2025
Uncertainty Quantification for Machine Learning in Healthcare: A Survey L. J. L. Lopez Shaza Elsharief Dhiyaa Al Jorf Firas Darwish Congbo Ma Farah E. Shamout 50 0 0 04 May 2025
Adversarial Examples in Environment Perception for Automated Driving (Review) Jun Yan Huilin Yin AAML 34 0 0 11 Apr 2025
The Disparate Benefits of Deep Ensembles Kajetan Schweighofer Adrián Arnaiz-Rodríguez Sepp Hochreiter Nuria Oliver FedML 18 1 0 17 Oct 2024
Probabilistic Degeneracy Detection for Point-to-Plane Error Minimization Johan Hatleskog Kostas Alexis 3DPC 30 0 0 14 Oct 2024
PH-Dropout: Practical Epistemic Uncertainty Quantification for View Synthesis Chuanhao Sun Thanos Triantafyllou Anthos Makris Maja Drmač Kai Xu Luo Mai Mahesh Marina 28 0 0 07 Oct 2024
Achieving Well-Informed Decision-Making in Drug Discovery: A Comprehensive Calibration Study using Neural Network-Based Structure-Activity Models Hannah Rosa Friesacher O. Engkvist Lewis H. Mervin Yves Moreau Adam Arany 24 0 0 19 Jul 2024
Semantically Diverse Language Generation for Uncertainty Estimation in Language Models L. Aichberger Kajetan Schweighofer Mykyta Ielanskyi Sepp Hochreiter HILM 23 10 0 06 Jun 2024
Epistemic Uncertainty Quantification For Pre-trained Neural Network Hanjing Wang Qiang Ji UQCV 20 2 0 15 Apr 2024
Out-of-Distribution Data: An Acquaintance of Adversarial Examples -- A Survey Naveen Karunanayake Ravin Gunawardena Suranga Seneviratne Sanjay Chawla OOD 35 5 0 08 Apr 2024
Introducing an Improved Information-Theoretic Measure of Predictive Uncertainty Kajetan Schweighofer L. Aichberger Mykyta Ielanskyi Sepp Hochreiter 8 11 0 14 Nov 2023
Laplacian Segmentation Networks: Improved Epistemic Uncertainty from Spatial Aleatoric Uncertainty Kilian Zepf Selma Wanna M. Miani Juston Moore J. Frellsen Søren Hauberg Aasa Feragen Frederik Warburg UQCV 13 4 0 23 Mar 2023
Variational Neural Networks Illia Oleksiienko D. Tran Alexandros Iosifidis BDL UQCV 21 8 0 04 Jul 2022
Multiple Importance Sampling ELBO and Deep Ensembles of Variational Approximations Oskar Kviman Harald Melin Hazal Koptagel Victor Elvira J. Lagergren DRL 63 17 0 22 Feb 2022
Which Shortcut Cues Will DNNs Choose? A Study from the Parameter-Space Perspective Luca Scimeca Seong Joon Oh Sanghyuk Chun Michael Poli Sangdoo Yun OOD 374 49 0 06 Oct 2021
Adversarial Examples, Uncertainty, and Transfer Testing Robustness in Gaussian Process Hybrid Deep Networks John Bradshaw A. G. Matthews Zoubin Ghahramani BDL AAML 60 171 0 08 Jul 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 268 5,652 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 247 9,109 0 06 Jun 2015