Error-Driven Uncertainty Aware Training

Error-Driven Uncertainty Aware Training

2 May 2024

Papers citing "Error-Driven Uncertainty Aware Training"

19 / 19 papers shown

Title
Training Uncertainty-Aware Classifiers with Conformalized Deep Learning Bat-Sheva Einbinder Yaniv Romano Matteo Sesia Yanfei Zhou UQCV 108 51 0 12 May 2022
The Devil is in the Margin: Margin-based Label Smoothing for Network Calibration Bingyuan Liu Ismail Ben Ayed Adrian Galdran Jose Dolz UQCV 66 69 0 30 Nov 2021
Soft Calibration Objectives for Neural Networks A. Karandikar Nicholas Cain Dustin Tran Balaji Lakshminarayanan Jonathon Shlens Michael C. Mozer Becca Roelofs UQCV 82 89 0 30 Jul 2021
A Survey of Uncertainty in Deep Neural Networks J. Gawlikowski Cedrique Rovile Njieutcheu Tassi Mohsin Ali Jongseo Lee Matthias Humt ... R. Roscher Muhammad Shahzad Wen Yang R. Bamler Xiaoxiang Zhu BDL UQCV OOD 229 1,149 0 07 Jul 2021
Objective Evaluation of Deep Uncertainty Predictions for COVID-19 Detection Hamzeh Asgharnezhad Afshar Shamsi Jokandan R. Alizadehsani Abbas Khosravi S. Nahavandi Z. Sani D. Srinivasan UQCV 60 71 0 22 Dec 2020
Improving model calibration with accuracy versus uncertainty optimization R. Krishnan Omesh Tickoo UQCV 245 164 0 14 Dec 2020
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges Moloud Abdar Farhad Pourpanah Sadiq Hussain Dana Rezazadegan Li Liu ... Xiaochun Cao Abbas Khosravi U. Acharya V. Makarenkov S. Nahavandi BDL UQCV 336 1,922 0 12 Nov 2020
Depth Uncertainty in Neural Networks Javier Antorán J. Allingham José Miguel Hernández-Lobato UQCV OOD BDL 76 101 0 15 Jun 2020
Calibrating Deep Neural Networks using Focal Loss Jishnu Mukhoti Viveka Kulharia Amartya Sanyal Stuart Golodetz Philip Torr P. Dokania UQCV 81 463 0 21 Feb 2020
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift Yaniv Ovadia Emily Fertig Jie Jessie Ren Zachary Nado D. Sculley Sebastian Nowozin Joshua V. Dillon Balaji Lakshminarayanan Jasper Snoek UQCV 167 1,695 0 06 Jun 2019
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations Dan Hendrycks Thomas G. Dietterich OOD VLM 172 3,435 0 28 Mar 2019
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 307 12,069 0 19 Jun 2017
Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods Nicholas Carlini D. Wagner AAML 121 1,857 0 20 May 2017
Detecting Adversarial Samples from Artifacts Reuben Feinman Ryan R. Curtin S. Shintre Andrew B. Gardner AAML 93 893 0 01 Mar 2017
Wide Residual Networks Sergey Zagoruyko N. Komodakis 340 7,985 0 23 May 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 821 9,318 0 06 Jun 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 277 19,066 0 20 Dec 2014
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 1.7K 39,547 0 01 Sep 2014
Deep Gaussian Processes Andreas C. Damianou Neil D. Lawrence GP BDL 127 1,182 0 02 Nov 2012

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