Benchmarking Uncertainty Disentanglement: Specialized Uncertainties for Specialized Tasks

29 February 2024

Papers citing "Benchmarking Uncertainty Disentanglement: Specialized Uncertainties for Specialized Tasks"

33 / 33 papers shown

Title
URL: A Representation Learning Benchmark for Transferable Uncertainty Estimates Michael Kirchhof Bálint Mucsányi Seong Joon Oh Enkelejda Kasneci UQCV 412 13 0 07 Jul 2023
A framework for benchmarking class-out-of-distribution detection and its application to ImageNet Ido Galil Mohammed Dabbah Ran El-Yaniv UQCV 34 29 0 23 Feb 2023
What Can We Learn From The Selective Prediction And Uncertainty Estimation Performance Of 523 Imagenet Classifiers Ido Galil Mohammed Dabbah Ran El-Yaniv UQCV 38 26 0 23 Feb 2023
Likelihood Annealing: Fast Calibrated Uncertainty for Regression Uddeshya Upadhyay Jae Myung Kim Cordelia Schmidt Bernhard Schölkopf Zeynep Akata BDL UQCV 41 1 0 21 Feb 2023
Probabilistic Contrastive Learning Recovers the Correct Aleatoric Uncertainty of Ambiguous Inputs Michael Kirchhof Enkelejda Kasneci Seong Joon Oh UQCV 399 22 0 06 Feb 2023
Massively Scaling Heteroscedastic Classifiers Mark Collier Rodolphe Jenatton Basil Mustafa N. Houlsby Jesse Berent E. Kokiopoulou 33 8 0 30 Jan 2023
On Second-Order Scoring Rules for Epistemic Uncertainty Quantification Viktor Bengs Eyke Hüllermeier Willem Waegeman UQCV 233 26 0 30 Jan 2023
Uncertainty Estimates of Predictions via a General Bias-Variance Decomposition Sebastian G. Gruber Florian Buettner PER UQCV UD 221 13 0 21 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 51 69 0 07 Sep 2022
Plex: Towards Reliability using Pretrained Large Model Extensions Dustin Tran J. Liu Michael W. Dusenberry Du Phan Mark Collier ... D. Sculley Y. Gal Zoubin Ghahramani Jasper Snoek Balaji Lakshminarayanan VLM 44 126 0 15 Jul 2022
Eliciting and Learning with Soft Labels from Every Annotator Katherine M. Collins Umang Bhatt Adrian Weller 37 44 0 02 Jul 2022
Ensembling over Classifiers: a Bias-Variance Perspective Neha Gupta Jamie Smith Ben Adlam Zelda E. Mariet FedML UQCV FaML 31 6 0 21 Jun 2022
A Deeper Look into Aleatoric and Epistemic Uncertainty Disentanglement Matias Valdenegro-Toro Daniel Saromo UD PER BDL UQCV 22 79 0 20 Apr 2022
Learning with Noisy Labels Revisited: A Study Using Real-World Human Annotations Jiaheng Wei Zhaowei Zhu Weiran Wang Tongliang Liu Gang Niu Yang Liu NoLa 58 247 0 22 Oct 2021
Ensemble-based Uncertainty Quantification: Bayesian versus Credal Inference M. Shaker Eyke Hüllermeier UD UQCV PER BDL 244 17 0 21 Jul 2021
On the Practicality of Deterministic Epistemic Uncertainty Janis Postels Mattia Segu Tao Sun Luca Sieber Luc Van Gool Feng Yu Federico Tombari UQCV 45 60 0 01 Jul 2021
Laplace Redux -- Effortless Bayesian Deep Learning Erik A. Daxberger Agustinus Kristiadi Alexander Immer Runa Eschenhagen Matthias Bauer Philipp Hennig BDL UQCV 63 299 0 28 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 38 96 0 07 Jun 2021
Deep Deterministic Uncertainty: A Simple Baseline Jishnu Mukhoti Andreas Kirsch Joost R. van Amersfoort Philip Torr Y. Gal UD UQCV PER BDL 42 148 0 23 Feb 2021
Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness Jeremiah Zhe Liu Zi Lin Shreyas Padhy Dustin Tran Tania Bedrax-Weiss Balaji Lakshminarayanan UQCV BDL 58 441 0 17 Jun 2020
Are we done with ImageNet? Lucas Beyer Olivier J. Hénaff Alexander Kolesnikov Xiaohua Zhai Aaron van den Oord VLM 56 399 0 12 Jun 2020
Human uncertainty makes classification more robust Joshua C. Peterson Ruairidh M. Battleday Thomas Griffiths Olga Russakovsky OOD 8 298 0 19 Aug 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 91 1,667 0 06 Jun 2019
Learning Loss for Active Learning Donggeun Yoo In So Kweon UQCV 44 655 0 09 May 2019
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations Dan Hendrycks Thomas G. Dietterich OOD VLM 17 3,386 0 28 Mar 2019
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks Kimin Lee Kibok Lee Honglak Lee Jinwoo Shin OODD 41 2,018 0 10 Jul 2018
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 348 5,742 0 05 Dec 2016
SGDR: Stochastic Gradient Descent with Warm Restarts I. Loshchilov Frank Hutter ODL 145 8,017 0 13 Aug 2016
Wide Residual Networks Sergey Zagoruyko N. Komodakis 142 7,944 0 23 May 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 658 192,387 0 10 Dec 2015
Why M Heads are Better than One: Training a Diverse Ensemble of Deep Networks Stefan Lee Senthil Purushwalkam Michael Cogswell David J. Crandall Dhruv Batra FedML UQCV 22 311 0 19 Nov 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 313 9,221 0 06 Jun 2015
Statistical Learning Theory: Models, Concepts, and Results U. V. Luxburg Bernhard Schölkopf 73 242 0 27 Oct 2008