Revisiting the Calibration of Modern Neural Networks

Revisiting the Calibration of Modern Neural Networks

15 June 2021

Matthias Minderer

Papers citing "Revisiting the Calibration of Modern Neural Networks"

19 / 69 papers shown

Title
Language Models (Mostly) Know What They Know Saurav Kadavath Tom Conerly Amanda Askell T. Henighan Dawn Drain ... Nicholas Joseph Benjamin Mann Sam McCandlish C. Olah Jared Kaplan ELM 44 712 0 11 Jul 2022
ProSelfLC: Progressive Self Label Correction Towards A Low-Temperature Entropy State Xinshao Wang Yang Hua Elyor Kodirov S. Mukherjee David A. Clifton N. Robertson 15 6 0 30 Jun 2022
Forecasting Future World Events with Neural Networks Andy Zou Tristan Xiao Ryan Jia Joe Kwon Mantas Mazeika Richard Li Dawn Song Jacob Steinhardt Owain Evans Dan Hendrycks 22 22 0 30 Jun 2022
COLD Fusion: Calibrated and Ordinal Latent Distribution Fusion for Uncertainty-Aware Multimodal Emotion Recognition M. Tellamekala Shahin Amiriparian Björn W. Schuller Elisabeth André T. Giesbrecht M. Valstar 23 25 0 12 Jun 2022
Re-Examining Calibration: The Case of Question Answering Chenglei Si Chen Zhao Sewon Min Jordan L. Boyd-Graber 59 30 0 25 May 2022
Calibration of Natural Language Understanding Models with Venn--ABERS Predictors Patrizio Giovannotti 38 6 0 21 May 2022
A General Framework for quantifying Aleatoric and Epistemic uncertainty in Graph Neural Networks Sai Munikoti D. Agarwal Laya Das Balasubramaniam Natarajan BDL UD 28 13 0 20 May 2022
Evaluating Uncertainty Calibration for Open-Set Recognition Zongyao Lyu Nolan B. Gutierrez William J. Beksi UQCV 27 1 0 15 May 2022
Distinction Maximization Loss: Efficiently Improving Out-of-Distribution Detection and Uncertainty Estimation by Replacing the Loss and Calibrating David Macêdo Cleber Zanchettin Teresa B Ludermir UQCV 25 4 0 12 May 2022
Calibrating for Class Weights by Modeling Machine Learning Andrew Caplin Daniel Martin Philip Marx 19 1 0 10 May 2022
It's DONE: Direct ONE-shot learning with quantile weight imprinting Kazufumi Hosoda Keigo Nishida S. Seno Tomohiro Mashita H. Kashioka I. Ohzawa 17 2 0 28 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 17 42 0 25 Mar 2022
How Do Vision Transformers Work? Namuk Park Songkuk Kim ViT 30 465 0 14 Feb 2022
On the Value of ML Models Fabio Casati Pierre-Andre Noel Jie Yang 11 7 0 13 Dec 2021
Deep Probability Estimation Sheng Liu Aakash Kaku Weicheng Zhu M. Leibovich S. Mohan ... Haoxiang Huang L. Zanna N. Razavian Jonathan Niles-Weed C. Fernandez‐Granda UQCV OOD 28 14 0 21 Nov 2021
Meta-Calibration: Learning of Model Calibration Using Differentiable Expected Calibration Error Ondrej Bohdal Yongxin Yang Timothy M. Hospedales UQCV OOD 37 21 0 17 Jun 2021
MLP-Mixer: An all-MLP Architecture for Vision Ilya O. Tolstikhin N. Houlsby Alexander Kolesnikov Lucas Beyer Xiaohua Zhai ... Andreas Steiner Daniel Keysers Jakob Uszkoreit Mario Lucic Alexey Dosovitskiy 271 2,603 0 04 May 2021
MetNet: A Neural Weather Model for Precipitation Forecasting C. Sønderby L. Espeholt Jonathan Heek Mostafa Dehghani Avital Oliver Tim Salimans Shreya Agrawal Jason Hickey Nal Kalchbrenner AI4Cl 219 273 0 24 Mar 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 270 5,660 0 05 Dec 2016