Verified Uncertainty Calibration

23 September 2019

Papers citing "Verified Uncertainty Calibration"

50 / 243 papers shown

Title
T-Cal: An optimal test for the calibration of predictive models Donghwan Lee Xinmeng Huang Hamed Hassani Yan Sun 22 20 0 03 Mar 2022
Confidence Calibration for Object Detection and Segmentation Fabian Küppers Anselm Haselhoff Jan Kronenberger Jonas Schneider UQCV 25 4 0 25 Feb 2022
Fourier-Based Augmentations for Improved Robustness and Uncertainty Calibration Ryan Soklaski Michael Yee Theodoros Tsiligkaridis AAML 22 14 0 24 Feb 2022
Taking a Step Back with KCal: Multi-Class Kernel-Based Calibration for Deep Neural Networks Zhen Lin Shubhendu Trivedi Jimeng Sun 35 5 0 15 Feb 2022
Conformal Prediction Sets with Limited False Positives Adam Fisch Tal Schuster Tommi Jaakkola Regina Barzilay 26 23 0 15 Feb 2022
Heterogeneous Calibration: A post-hoc model-agnostic framework for improved generalization D. Durfee Aman Gupta Kinjal Basu UQCV 19 2 0 10 Feb 2022
Hidden Heterogeneity: When to Choose Similarity-Based Calibration K. Wagstaff Thomas G. Dietterich 29 1 0 03 Feb 2022
On the relationship between calibrated predictors and unbiased volume estimation Teodora Popordanoska J. Bertels Dirk Vandermeulen F. Maes Matthew B. Blaschko 42 11 0 23 Dec 2021
Classifier Calibration: A survey on how to assess and improve predicted class probabilities Telmo de Menezes e Silva Filho Hao Song Miquel Perelló Nieto Raúl Santos-Rodríguez Meelis Kull Peter A. Flach 40 79 0 20 Dec 2021
Benchmarking Uncertainty Quantification on Biosignal Classification Tasks under Dataset Shift Tong Xia Jing Han Cecilia Mascolo OOD 24 11 0 16 Dec 2021
The Box Size Confidence Bias Harms Your Object Detector Johannes Gilg Torben Teepe Fabian Herzog Gerhard Rigoll ObjD 21 4 0 03 Dec 2021
TransMix: Attend to Mix for Vision Transformers Jieneng Chen Shuyang Sun Ju He Philip Torr Alan Yuille S. Bai ViT 30 103 0 18 Nov 2021
SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Robustness Jongheon Jeong Sejun Park Minkyu Kim Heung-Chang Lee Do-Guk Kim Jinwoo Shin AAML 31 55 0 17 Nov 2021
Scaffolding Sets M. Burhanpurkar Zhun Deng Cynthia Dwork Linjun Zhang 41 9 0 04 Nov 2021
Exploring Covariate and Concept Shift for Detection and Calibration of Out-of-Distribution Data Junjiao Tian Yen-Change Hsu Yilin Shen Hongxia Jin Z. Kira OODD 19 6 0 28 Oct 2021
Reliable Probability Intervals For Classification Using Inductive Venn Predictors Based on Distance Learning Dimitrios Boursinos X. Koutsoukos 13 1 0 07 Oct 2021
Assurance Monitoring of Learning Enabled Cyber-Physical Systems Using Inductive Conformal Prediction based on Distance Learning Dimitrios Boursinos X. Koutsoukos 46 11 0 07 Oct 2021
Post-hoc Models for Performance Estimation of Machine Learning Inference Xuechen Zhang Samet Oymak Jiasi Chen UQCV 21 4 0 06 Oct 2021
Combining Human Predictions with Model Probabilities via Confusion Matrices and Calibration Gavin Kerrigan Padhraic Smyth M. Steyvers 30 48 0 29 Sep 2021
Unsolved Problems in ML Safety Dan Hendrycks Nicholas Carlini John Schulman Jacob Steinhardt 186 276 0 28 Sep 2021
When in Doubt: Improving Classification Performance with Alternating Normalization Menglin Jia A. Reiter Ser-Nam Lim Yoav Artzi Claire Cardie 30 13 0 28 Sep 2021
Making Heads and Tails of Models with Marginal Calibration for Sparse Tagsets Michael Kranzlein Nelson F. Liu Nathan Schneider 14 3 0 15 Sep 2021
DROMO: Distributionally Robust Offline Model-based Policy Optimization Ruizhen Liu Dazhi Zhong Zhi-Cong Chen OffRL 34 3 0 15 Sep 2021
Soft Calibration Objectives for Neural Networks A. Karandikar Nicholas Cain Dustin Tran Balaji Lakshminarayanan Jonathon Shlens Michael C. Mozer Becca Roelofs UQCV 25 85 0 30 Jul 2021
Top-label calibration and multiclass-to-binary reductions Chirag Gupta Aaditya Ramdas 25 35 0 18 Jul 2021
Towards Robust Active Feature Acquisition Yang Li Siyuan Shan Qin Liu Junier B. Oliva TPM 18 4 0 09 Jul 2021
Assessing Generalization of SGD via Disagreement Yiding Jiang Vaishnavh Nagarajan Christina Baek J. Zico Kolter 67 109 0 25 Jun 2021
PAC Prediction Sets Under Covariate Shift Sangdon Park Yan Sun Insup Lee Osbert Bastani 34 43 0 17 Jun 2021
Meta-Calibration: Learning of Model Calibration Using Differentiable Expected Calibration Error Ondrej Bohdal Yongxin Yang Timothy M. Hospedales UQCV OOD 45 21 0 17 Jun 2021
On Deep Neural Network Calibration by Regularization and its Impact on Refinement Aditya Singh Alessandro Bay B. Sengupta Andrea Mirabile AAML 27 2 0 17 Jun 2021
To Raise or Not To Raise: The Autonomous Learning Rate Question Xiaomeng Dong Tao Tan Michael Potter Yun-Chan Tsai Gaurav Kumar V. R. Saripalli Theodore Trafalis OOD 13 2 0 16 Jun 2021
Revisiting the Calibration of Modern Neural Networks Matthias Minderer Josip Djolonga Rob Romijnders F. Hubis Xiaohua Zhai N. Houlsby Dustin Tran Mario Lucic UQCV 51 358 0 15 Jun 2021
Understanding the Under-Coverage Bias in Uncertainty Estimation Yu Bai Song Mei Huan Wang Caiming Xiong UQCV 15 13 0 10 Jun 2021
Can a single neuron learn predictive uncertainty? Edgardo Solano-Carrillo UQCV 29 1 0 07 Jun 2021
Distribution-free calibration guarantees for histogram binning without sample splitting Chirag Gupta Aaditya Ramdas 27 37 0 10 May 2021
Meta-Cal: Well-controlled Post-hoc Calibration by Ranking Xingchen Ma Matthew B. Blaschko 28 34 0 10 May 2021
Uncertainty-Aware Boosted Ensembling in Multi-Modal Settings U. Sarawgi Rishab Khincha W. Zulfikar Satrajit S. Ghosh Pattie Maes UQCV 25 7 0 21 Apr 2021
von Mises-Fisher Loss: An Exploration of Embedding Geometries for Supervised Learning Tyler R. Scott Andrew C. Gallagher Michael C. Mozer 29 39 0 29 Mar 2021
SCRIB: Set-classifier with Class-specific Risk Bounds for Blackbox Models Zhen Lin Cao Xiao Lucas Glass M. P. M. Brandon Westover Jimeng Sun BDL 29 11 0 05 Mar 2021
Distribution-free uncertainty quantification for classification under label shift Aleksandr Podkopaev Aaditya Ramdas UQCV 22 86 0 04 Mar 2021
Confidence Calibration with Bounded Error Using Transformations Sooyong Jang Radoslav Ivanov Insup Lee James Weimer UQCV 11 3 0 25 Feb 2021
Parameterized Temperature Scaling for Boosting the Expressive Power in Post-Hoc Uncertainty Calibration Christian Tomani Daniel Cremers Florian Buettner UQCV 21 33 0 24 Feb 2021
Don't Just Blame Over-parametrization for Over-confidence: Theoretical Analysis of Calibration in Binary Classification Yu Bai Song Mei Haiquan Wang Caiming Xiong 17 42 0 15 Feb 2021
When and How Mixup Improves Calibration Linjun Zhang Zhun Deng Kenji Kawaguchi James Zou UQCV 36 67 0 11 Feb 2021
Joint Energy-based Model Training for Better Calibrated Natural Language Understanding Models Tianxing He Bryan McCann Caiming Xiong Ehsan Hosseini-Asl 12 19 0 18 Jan 2021
Should Ensemble Members Be Calibrated? Xixin Wu Mark Gales UQCV 23 12 0 13 Jan 2021
Estimating and Evaluating Regression Predictive Uncertainty in Deep Object Detectors Ali Harakeh Steven L. Waslander UQCV 19 41 0 13 Jan 2021
From Black-box to White-box: Examining Confidence Calibration under different Conditions Franziska Schwaiger Maximilian Henne Fabian Küppers Felippe Schmoeller da Roza Karsten Roscher Anselm Haselhoff 34 10 0 08 Jan 2021
Post-hoc Uncertainty Calibration for Domain Drift Scenarios Christian Tomani Sebastian Gruber Muhammed Ebrar Erdem Daniel Cremers Florian Buettner UQCV 33 66 0 20 Dec 2020
Towards Trustworthy Predictions from Deep Neural Networks with Fast Adversarial Calibration Christian Tomani Florian Buettner UQCV AAML OOD 27 39 0 20 Dec 2020