ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1902.06977
  4. Cited By
Evaluating model calibration in classification

Evaluating model calibration in classification

19 February 2019
Juozas Vaicenavicius
David Widmann
Carl R. Andersson
Fredrik Lindsten
Jacob Roll
Thomas B. Schon
    UQCV
ArXivPDFHTML

Papers citing "Evaluating model calibration in classification"

12 / 62 papers shown
Title
Calibrating Structured Output Predictors for Natural Language Processing
Calibrating Structured Output Predictors for Natural Language Processing
Abhyuday N. Jagannatha
Hong-ye Yu
27
28
0
09 Apr 2020
A Unified View of Label Shift Estimation
A Unified View of Label Shift Estimation
Saurabh Garg
Yifan Wu
Sivaraman Balakrishnan
Zachary Chase Lipton
24
141
0
17 Mar 2020
Mix-n-Match: Ensemble and Compositional Methods for Uncertainty
  Calibration in Deep Learning
Mix-n-Match: Ensemble and Compositional Methods for Uncertainty Calibration in Deep Learning
Jize Zhang
B. Kailkhura
T. Y. Han
UQCV
30
219
0
16 Mar 2020
Calibrating Deep Neural Networks using Focal Loss
Calibrating Deep Neural Networks using Focal Loss
Jishnu Mukhoti
Viveka Kulharia
Amartya Sanyal
Stuart Golodetz
Philip Torr
P. Dokania
UQCV
56
448
0
21 Feb 2020
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep
  Learning
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning
Arsenii Ashukha
Alexander Lyzhov
Dmitry Molchanov
Dmitry Vetrov
UQCV
FedML
38
314
0
15 Feb 2020
Beyond temperature scaling: Obtaining well-calibrated multiclass
  probabilities with Dirichlet calibration
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
31
373
0
28 Oct 2019
Calibration tests in multi-class classification: A unifying framework
Calibration tests in multi-class classification: A unifying framework
David Widmann
Fredrik Lindsten
Dave Zachariah
23
92
0
24 Oct 2019
Verified Uncertainty Calibration
Verified Uncertainty Calibration
Ananya Kumar
Percy Liang
Tengyu Ma
33
347
0
23 Sep 2019
Non-Parametric Calibration for Classification
Non-Parametric Calibration for Classification
Jonathan Wenger
Hedvig Kjellström
Rudolph Triebel
UQCV
50
79
0
12 Jun 2019
Measuring Calibration in Deep Learning
Measuring Calibration in Deep Learning
Jeremy Nixon
Michael W. Dusenberry
Ghassen Jerfel
Timothy Nguyen
Jeremiah Zhe Liu
Linchuan Zhang
Dustin Tran
UQCV
36
479
0
02 Apr 2019
Maximum Likelihood with Bias-Corrected Calibration is Hard-To-Beat at
  Label Shift Adaptation
Maximum Likelihood with Bias-Corrected Calibration is Hard-To-Beat at Label Shift Adaptation
Amr M. Alexandari
A. Kundaje
Avanti Shrikumar
21
9
0
21 Jan 2019
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
278
5,695
0
05 Dec 2016
Previous
12