Measuring Calibration in Deep Learning

2 April 2019

Jeremy Nixon

Michael W. Dusenberry

Papers citing "Measuring Calibration in Deep Learning"

50 / 310 papers shown

Title
Calibrate: Interactive Analysis of Probabilistic Model Output Peter Xenopoulos Joao Rulff L. G. Nonato Brian Barr Claudio Silva 19 13 0 27 Jul 2022
MedML: Fusing Medical Knowledge and Machine Learning Models for Early Pediatric COVID-19 Hospitalization and Severity Prediction Junyi Gao Chaoqi Yang George Heintz Scott Barrows E.A. Albers Mary Stapel Sara C Warfield Adam Cross Jimeng Sun The N3C Consortium 15 27 0 25 Jul 2022
Aries: Efficient Testing of Deep Neural Networks via Labeling-Free Accuracy Estimation Qiang Hu Yuejun Guo Xiaofei Xie Maxime Cordy Lei Ma Mike Papadakis Yves Le Traon AAML 20 18 0 22 Jul 2022
Assaying Out-Of-Distribution Generalization in Transfer Learning F. Wenzel Andrea Dittadi Peter V. Gehler Carl-Johann Simon-Gabriel Max Horn ... Chris Russell Thomas Brox Bernt Schiele Bernhard Schölkopf Francesco Locatello OOD OODD AAML 64 71 0 19 Jul 2022
Angular Gap: Reducing the Uncertainty of Image Difficulty through Model Calibration Bohua Peng Mobarakol Islam Mei Tu UQCV 21 9 0 18 Jul 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 39 124 0 15 Jul 2022
Sample-dependent Adaptive Temperature Scaling for Improved Calibration Thomas Joy Francesco Pinto Ser-Nam Lim Philip Torr P. Dokania UQCV 32 31 0 13 Jul 2022
Robust Bayesian Learning for Reliable Wireless AI: Framework and Applications Matteo Zecchin Sangwoo Park Osvaldo Simeone Marios Kountouris David Gesbert 8 15 0 01 Jul 2022
Uncertainty-aware Panoptic Segmentation Kshitij Sirohi Sajad Marvi Daniel Buscher Wolfram Burgard EDL UQCV 33 26 0 29 Jun 2022
Robustness to corruption in pre-trained Bayesian neural networks Xi Wang Laurence Aitchison OOD UQCV 22 5 0 24 Jun 2022
Which models are innately best at uncertainty estimation? Ido Galil Mohammed Dabbah Ran El-Yaniv UQCV 34 5 0 05 Jun 2022
Excess risk analysis for epistemic uncertainty with application to variational inference Futoshi Futami Tomoharu Iwata N. Ueda Issei Sato Masashi Sugiyama UQCV 31 1 0 02 Jun 2022
FiLM-Ensemble: Probabilistic Deep Learning via Feature-wise Linear Modulation Mehmet Özgür Türkoglu Alexander Becker H. Gündüz Mina Rezaei Bernd Bischl Rodrigo Caye Daudt Stefano Dáronco Jan Dirk Wegner Konrad Schindler FedML UQCV 45 25 0 31 May 2022
Going Beyond One-Hot Encoding in Classification: Can Human Uncertainty Improve Model Performance? Christoph Koller Goran Kauermann Xiao Xiang Zhu UQCV 24 6 0 30 May 2022
Teaching Models to Express Their Uncertainty in Words Stephanie C. Lin Jacob Hilton Owain Evans OOD 35 368 0 28 May 2022
Re-Examining Calibration: The Case of Question Answering Chenglei Si Chen Zhao Sewon Min Jordan L. Boyd-Graber 67 30 0 25 May 2022
What is Your Metric Telling You? Evaluating Classifier Calibration under Context-Specific Definitions of Reliability John Kirchenbauer Jacob Oaks Eric Heim UQCV 38 4 0 23 May 2022
Robust Flow-based Conformal Inference (FCI) with Statistical Guarantee Youhui Ye Meimei Liu Xin Xing 23 0 0 22 May 2022
Metrics of calibration for probabilistic predictions Imanol Arrieta-Ibarra Paman Gujral Jonathan Tannen M. Tygert Cherie Xu 55 20 0 19 May 2022
A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness J. Liu Shreyas Padhy Jie Jessie Ren Zi Lin Yeming Wen Ghassen Jerfel Zachary Nado Jasper Snoek Dustin Tran Balaji Lakshminarayanan UQCV BDL 26 48 0 01 May 2022
Is my Driver Observation Model Overconfident? Input-guided Calibration Networks for Reliable and Interpretable Confidence Estimates Alina Roitberg Kunyu Peng David Schneider Kailun Yang Marios Koulakis Manuel Martínez Rainer Stiefelhagen UQCV 30 9 0 10 Apr 2022
DBCal: Density Based Calibration of classifier predictions for uncertainty quantification A. Hagen K. Pazdernik Nicole LaHaye Marjolein Oostrom UQCV 17 2 0 01 Apr 2022
A Stitch in Time Saves Nine: A Train-Time Regularizing Loss for Improved Neural Network Calibration R. Hebbalaguppe Jatin Prakash Neelabh Madan Chetan Arora UQCV 25 42 0 25 Mar 2022
Calibration Error for Heterogeneous Treatment Effects Yizhe Xu Steve Yadlowsky 33 12 0 24 Mar 2022
Improving the Fairness of Chest X-ray Classifiers Haoran Zhang Natalie Dullerud Karsten Roth Lauren Oakden-Rayner Stephen R. Pfohl Marzyeh Ghassemi 23 65 0 23 Mar 2022
On the Usefulness of the Fit-on-the-Test View on Evaluating Calibration of Classifiers Markus Kängsepp Kaspar Valk Meelis Kull 35 3 0 16 Mar 2022
Better Uncertainty Calibration via Proper Scores for Classification and Beyond Sebastian G. Gruber Florian Buettner UQCV 14 45 0 15 Mar 2022
T-Cal: An optimal test for the calibration of predictive models Donghwan Lee Xinmeng Huang Hamed Hassani Yan Sun 24 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
UncertaINR: Uncertainty Quantification of End-to-End Implicit Neural Representations for Computed Tomography Francisca Vasconcelos Bobby He Nalini Singh Yee Whye Teh BDL OOD UQCV 37 12 0 22 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
A Note on "Assessing Generalization of SGD via Disagreement" Andreas Kirsch Y. Gal FedML UQCV 26 15 0 03 Feb 2022
Hidden Heterogeneity: When to Choose Similarity-Based Calibration K. Wagstaff Thomas G. Dietterich 29 1 0 03 Feb 2022
Metrics for saliency map evaluation of deep learning explanation methods T. Gomez Thomas Fréour Harold Mouchère XAI FAtt 69 41 0 31 Jan 2022
Barely-Supervised Learning: Semi-Supervised Learning with very few labeled images Thomas Lucas Philippe Weinzaepfel Grégory Rogez SSL 30 30 0 22 Dec 2021
Improving evidential deep learning via multi-task learning Dongpin Oh Bonggun Shin EDL UQCV 27 24 0 17 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
Why Calibration Error is Wrong Given Model Uncertainty: Using Posterior Predictive Checks with Deep Learning Achintya Gopal UQCV 30 1 0 02 Dec 2021
Case-based off-policy policy evaluation using prototype learning Anton Matsson Fredrik D. Johansson OffRL 6 1 0 22 Nov 2021
Exploiting all samples in low-resource sentence classification: early stopping and initialization parameters Hongseok Choi Hyunju Lee 29 3 0 12 Nov 2021
The Science of Rejection: A Research Area for Human Computation Burcu Sayin Jie Yang Andrea Passerini Fabio Casati HAI 16 5 0 11 Nov 2021
Towards Calibrated Model for Long-Tailed Visual Recognition from Prior Perspective Zhengzhuo Xu Zenghao Chai Chun Yuan 70 52 0 06 Nov 2021
On the use of uncertainty in classifying Aedes Albopictus mosquitoes Gereziher W. Adhane Mohammad Mahdi Dehshibi David Masip 25 7 0 29 Oct 2021
Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation Dennis Ulmer Christian Hardmeier J. Frellsen BDL UQCV UD EDL PER 55 48 0 06 Oct 2021
Does deep learning model calibration improve performance in class-imbalanced medical image classification? S. Rajaraman Prasanth Ganesan Sameer Kiran Antani 196 39 0 29 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
Class-Distribution-Aware Calibration for Long-Tailed Visual Recognition Mobarakol Islam Lalithkumar Seenivasan Hongliang Ren Ben Glocker 31 18 0 11 Sep 2021
Estimating Expected Calibration Errors N. Posocco Antoine Bonnefoy 13 15 0 08 Sep 2021
MACEst: The reliable and trustworthy Model Agnostic Confidence Estimator Rhys Green Matthew Rowe A. Polleri 17 3 0 02 Sep 2021
Effect of the output activation function on the probabilities and errors in medical image segmentation Lars Nieradzik G. Scheuermann D. Saur Christina Gillmann SSeg MedIm UQCV 35 6 0 02 Sep 2021