Sample-dependent Adaptive Temperature Scaling for Improved Calibration

Sample-dependent Adaptive Temperature Scaling for Improved Calibration

13 July 2022

Francesco Pinto

Ser-Nam Lim

Philip H. S. Torr

Papers citing "Sample-dependent Adaptive Temperature Scaling for Improved Calibration"

9 / 9 papers shown

Title
Restoring Calibration for Aligned Large Language Models: A Calibration-Aware Fine-Tuning Approach Jiancong Xiao Bojian Hou Zhanliang Wang Ruochen Jin Q. Long Weijie Su Li Shen 28 0 0 04 May 2025
Optical aberrations in autonomous driving: Physics-informed parameterized temperature scaling for neural network uncertainty calibration D. Wolf Alexander Braun Markus Ulrich 89 0 0 18 Dec 2024
Combining Priors with Experience: Confidence Calibration Based on Binomial Process Modeling Jinzong Dong Zhaohui Jiang Dong Pan Haoyang Yu 49 0 0 14 Dec 2024
Can Large Language Models Invent Algorithms to Improve Themselves? Yoichi Ishibashi Taro Yano Masafumi Oyamada AIFin LRM 31 1 0 21 Oct 2024
Reassessing How to Compare and Improve the Calibration of Machine Learning Models M. Chidambaram Rong Ge 63 1 0 06 Jun 2024
Optimizing Calibration by Gaining Aware of Prediction Correctness Yuchi Liu Lei Wang Yuli Zou James Zou Liang Zheng UQCV 37 1 0 19 Apr 2024
Accuracy-Preserving Calibration via Statistical Modeling on Probability Simplex Yasushi Esaki Akihiro Nakamura Keisuke Kawano Ryoko Tokuhisa Takuro Kutsuna 28 0 0 21 Feb 2024
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 268 5,635 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 247 9,042 0 06 Jun 2015