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Unified Uncertainty Calibration

2 October 2023

Papers citing "Unified Uncertainty Calibration"

25 / 25 papers shown

Title
Estimating Soft Labels for Out-of-Domain Intent Detection Hao Lang Yinhe Zheng Jian Sun Feiling Huang Luo Si Yongbin Li 60 15 0 10 Nov 2022
Robust Calibration with Multi-domain Temperature Scaling Yaodong Yu Stephen Bates Yi-An Ma Michael I. Jordan OOD UQCV 73 34 0 06 Jun 2022
Mitigating Neural Network Overconfidence with Logit Normalization Hongxin Wei Renchunzi Xie Hao-Ran Cheng Lei Feng Bo An Yixuan Li OODD 220 285 0 19 May 2022
Out-of-Distribution Detection with Deep Nearest Neighbors Yiyou Sun Yifei Ming Xiaojin Zhu Yixuan Li OODD 200 520 0 13 Apr 2022
A Survey of Uncertainty in Deep Neural Networks J. Gawlikowski Cedrique Rovile Njieutcheu Tassi Mohsin Ali Jongseo Lee Matthias Humt ... R. Roscher Muhammad Shahzad Wen Yang R. Bamler Xiaoxiang Zhu BDL UQCV OOD 229 1,150 0 07 Jul 2021
A Simple Fix to Mahalanobis Distance for Improving Near-OOD Detection Jie Jessie Ren Stanislav Fort J. Liu Abhijit Guha Roy Shreyas Padhy Balaji Lakshminarayanan UQCV 173 225 0 16 Jun 2021
Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning Zachary Nado Neil Band Mark Collier Josip Djolonga Michael W. Dusenberry ... D. Sculley Balaji Lakshminarayanan Jasper Snoek Y. Gal Dustin Tran UQCV ELM 83 96 0 07 Jun 2021
Gradient Starvation: A Learning Proclivity in Neural Networks Mohammad Pezeshki Sekouba Kaba Yoshua Bengio Aaron Courville Doina Precup Guillaume Lajoie MLT 128 268 0 18 Nov 2020
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges Moloud Abdar Farhad Pourpanah Sadiq Hussain Dana Rezazadegan Li Liu ... Xiaochun Cao Abbas Khosravi U. Acharya V. Makarenkov S. Nahavandi BDL UQCV 343 1,928 0 12 Nov 2020
Training independent subnetworks for robust prediction Marton Havasi Rodolphe Jenatton Stanislav Fort Jeremiah Zhe Liu Jasper Snoek Balaji Lakshminarayanan Andrew M. Dai Dustin Tran UQCV OOD 85 213 0 13 Oct 2020
A Unifying Review of Deep and Shallow Anomaly Detection Lukas Ruff Jacob R. Kauffmann Robert A. Vandermeulen G. Montavon Wojciech Samek Marius Kloft Thomas G. Dietterich Klaus-Robert Muller UQCV 117 800 0 24 Sep 2020
The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalization Dan Hendrycks Steven Basart Norman Mu Saurav Kadavath Frank Wang ... Samyak Parajuli Mike Guo Basel Alomair Jacob Steinhardt Justin Gilmer OOD 347 1,751 0 29 Jun 2020
The Pitfalls of Simplicity Bias in Neural Networks Harshay Shah Kaustav Tamuly Aditi Raghunathan Prateek Jain Praneeth Netrapalli AAML 69 361 0 13 Jun 2020
Scaling Out-of-Distribution Detection for Real-World Settings Dan Hendrycks Steven Basart Mantas Mazeika Andy Zou Joe Kwon Mohammadreza Mostajabi Jacob Steinhardt Basel Alomair OODD 180 481 0 25 Nov 2019
Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods Eyke Hüllermeier Willem Waegeman PER UD 244 1,421 0 21 Oct 2019
Natural Adversarial Examples Dan Hendrycks Kevin Zhao Steven Basart Jacob Steinhardt Basel Alomair OODD 212 1,482 0 16 Jul 2019
Invariant Risk Minimization Martín Arjovsky Léon Bottou Ishaan Gulrajani David Lopez-Paz OOD 192 2,241 0 05 Jul 2019
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift Yaniv Ovadia Emily Fertig Jie Jessie Ren Zachary Nado D. Sculley Sebastian Nowozin Joshua V. Dillon Balaji Lakshminarayanan Jasper Snoek UQCV 170 1,704 0 06 Jun 2019
Do ImageNet Classifiers Generalize to ImageNet? Benjamin Recht Rebecca Roelofs Ludwig Schmidt Vaishaal Shankar OOD SSeg VLM 116 1,726 0 13 Feb 2019
Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem Matthias Hein Maksym Andriushchenko Julian Bitterwolf OODD 170 558 0 13 Dec 2018
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks Kimin Lee Kibok Lee Honglak Lee Jinwoo Shin OODD 187 2,060 0 10 Jul 2018
mixup: Beyond Empirical Risk Minimization Hongyi Zhang Moustapha Cissé Yann N. Dauphin David Lopez-Paz NoLa 280 9,797 0 25 Oct 2017
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? Alex Kendall Y. Gal BDL OOD UD UQCV PER 359 4,718 0 15 Mar 2017
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 831 9,345 0 06 Jun 2015
Describing Textures in the Wild Mircea Cimpoi Subhransu Maji Iasonas Kokkinos S. Mohamed Andrea Vedaldi 3DV 138 2,686 0 14 Nov 2013