Evaluating model calibration in classification

19 February 2019

Fredrik Lindsten

Papers citing "Evaluating model calibration in classification"

27 / 127 papers shown

Title
Should Ensemble Members Be Calibrated? Xixin Wu Mark Gales UQCV 51 12 0 13 Jan 2021
Combining Ensembles and Data Augmentation can Harm your Calibration Yeming Wen Ghassen Jerfel Rafael Muller Michael W. Dusenberry Jasper Snoek Balaji Lakshminarayanan Dustin Tran UQCV 136 64 0 19 Oct 2020
A Generic Methodology for the Statistically Uniform & Comparable Evaluation of Automated Trading Platform Components A. Sokolovsky Luca Arnaboldi 38 3 0 21 Sep 2020
Diagnostic Uncertainty Calibration: Towards Reliable Machine Predictions in Medical Domain Takahiro Mimori Keiko Sasada H. Matsui Issei Sato UQCV 80 7 0 03 Jul 2020
Multi-Class Uncertainty Calibration via Mutual Information Maximization-based Binning Kanil Patel William H. Beluch Binh Yang Michael Pfeiffer Dan Zhang UQCV 113 34 0 23 Jun 2020
Calibration of Neural Networks using Splines Kartik Gupta Amir M. Rahimi Thalaiyasingam Ajanthan Thomas Mensink C. Sminchisescu Leonid Sigal 97 109 0 23 Jun 2020
Calibration of Model Uncertainty for Dropout Variational Inference M. Laves Sontje Ihler Karl-Philipp Kortmann T. Ortmaier BDL UQCV 121 18 0 20 Jun 2020
Distribution-free binary classification: prediction sets, confidence intervals and calibration Chirag Gupta Aleksandr Podkopaev Aaditya Ramdas UQCV 117 83 0 18 Jun 2020
Classification with Valid and Adaptive Coverage Yaniv Romano Matteo Sesia Emmanuel J. Candès 397 329 0 03 Jun 2020
Plots of the cumulative differences between observed and expected values of ordered Bernoulli variates M. Tygert UQCV 20 4 0 03 Jun 2020
Calibrating Structured Output Predictors for Natural Language Processing Abhyuday N. Jagannatha Hong-ye Yu 103 28 0 09 Apr 2020
A Unified View of Label Shift Estimation Saurabh Garg Yifan Wu Sivaraman Balakrishnan Zachary Chase Lipton 99 146 0 17 Mar 2020
Mix-n-Match: Ensemble and Compositional Methods for Uncertainty Calibration in Deep Learning Jize Zhang B. Kailkhura T. Y. Han UQCV 106 227 0 16 Mar 2020
Quantile Regularization: Towards Implicit Calibration of Regression Models Saiteja Utpala Piyush Rai UQCV 53 8 0 28 Feb 2020
Calibrating Deep Neural Networks using Focal Loss Jishnu Mukhoti Viveka Kulharia Amartya Sanyal Stuart Golodetz Philip Torr P. Dokania UQCV 94 467 0 21 Feb 2020
Active Bayesian Assessment for Black-Box Classifiers Disi Ji Robert L Logan IV Padhraic Smyth M. Steyvers UQCV 41 17 0 16 Feb 2020
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning Arsenii Ashukha Alexander Lyzhov Dmitry Molchanov Dmitry Vetrov UQCV FedML 96 320 0 15 Feb 2020
A multiple testing framework for diagnostic accuracy studies with co-primary endpoints Max Westphal A. Zapf W. Brannath 27 5 0 08 Nov 2019
Beyond temperature scaling: Obtaining well-calibrated multiclass probabilities with Dirichlet calibration Meelis Kull Miquel Perelló Nieto Markus Kängsepp Telmo de Menezes e Silva Filho Hao Song Peter A. Flach UQCV 103 384 0 28 Oct 2019
Calibration tests in multi-class classification: A unifying framework David Widmann Fredrik Lindsten Dave Zachariah 97 94 0 24 Oct 2019
Verified Uncertainty Calibration Ananya Kumar Percy Liang Tengyu Ma 192 359 0 23 Sep 2019
Non-Parametric Calibration for Classification Jonathan Wenger Hedvig Kjellström Rudolph Triebel UQCV 118 82 0 12 Jun 2019
Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer Vision Fredrik K. Gustafsson Martin Danelljan Thomas B. Schon OOD UQCV BDL 80 301 0 04 Jun 2019
Are Graph Neural Networks Miscalibrated? Leonardo Teixeira B. Jalaeian Bruno Ribeiro AI4CE 75 22 0 07 May 2019
Measuring Calibration in Deep Learning Jeremy Nixon Michael W. Dusenberry Ghassen Jerfel Timothy Nguyen Jeremiah Zhe Liu Linchuan Zhang Dustin Tran UQCV 96 492 0 02 Apr 2019
Revisiting the Evaluation of Uncertainty Estimation and Its Application to Explore Model Complexity-Uncertainty Trade-Off Yukun Ding Jinglan Liu Jinjun Xiong Yiyu Shi 49 13 0 05 Mar 2019
Maximum Likelihood with Bias-Corrected Calibration is Hard-To-Beat at Label Shift Adaptation Amr M. Alexandari A. Kundaje Avanti Shrikumar 52 9 0 21 Jan 2019