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References (16)

[1]
Where are we with calibration under dataset shift in image classification?
2025Mélanie Roschewitz, Raghav Mehta et al.
[2]
RankMixup: Ranking-Based Mixup Training for Network Calibration
2023Jongyoun Noh, Hyekang Park et al.
[3]
Sample-dependent Adaptive Temperature Scaling for Improved Calibration
2022Thomas Joy, Francesco Pinto et al.
[4]
Revisiting the Calibration of Modern Neural Networks
2021M. Minderer, J. Djolonga et al.
[5]
Beyond temperature scaling: Obtaining well-calibrated multiclass probabilities with Dirichlet calibration
2019Meelis Kull, Miquel Perello-Nieto et al.
[6]
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift
2019Yaniv Ovadia, Emily Fertig et al.
[7]
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations
2019Dan Hendrycks, Thomas G. Dietterich
[8]
Attended Temperature Scaling: A Practical Approach for Calibrating Deep Neural Networks
2018A. Mozafari, H. Gomes et al.
[9]
Neural Ordinary Differential Equations
2018T. Chen, Yulia Rubanova et al.
[10]
On Calibration of Modern Neural Networks
2017Chuan Guo, Geoff Pleiss et al.
[11]
Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer
2017Noam Shazeer, Azalia Mirhoseini et al.
[12]
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
2016Balaji Lakshminarayanan, A. Pritzel et al.
[13]
Feedback Control Of Dynamic Systems
2016Yvonne Schuhmacher
[14]
Deep Residual Learning for Image Recognition
2015Kaiming He, X. Zhang et al.
[15]
Obtaining Well Calibrated Probabilities Using Bayesian Binning
2015Mahdi Pakdaman Naeini, G. Cooper et al.
[16]
Learning Multiple Layers of Features from Tiny Images
2009A. Krizhevsky

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