Human uncertainty makes classification more robust

19 August 2019

Joshua C. Peterson

Ruairidh M. Battleday

Papers citing "Human uncertainty makes classification more robust"

36 / 36 papers shown

Title
Uncertainty Weighted Gradients for Model Calibration Jinxu Lin Linwei Tao Minjing Dong Chang Xu UQCV 108 0 0 26 Mar 2025
Subjective Logic Encodings Jake Vasilakes Chrysoula Zerva Sophia Ananiadou 94 0 0 17 Feb 2025
Training and Evaluating with Human Label Variation: An Empirical Study Kemal Kurniawan Meladel Mistica Timothy Baldwin Jey Han Lau 87 1 0 03 Feb 2025
Measuring Error Alignment for Decision-Making Systems Binxia Xu Antonis Bikakis Daniel Onah A. Vlachidis Luke Dickens 71 0 0 03 Jan 2025
Seeking Consistent Flat Minima for Better Domain Generalization via Refining Loss Landscapes Aodi Li Liansheng Zhuang Xiao Long Minghong Yao Shafei Wang 418 0 0 18 Dec 2024
Conformalized Credal Regions for Classification with Ambiguous Ground Truth Michele Caprio David Stutz Shuo Li Arnaud Doucet UQCV 184 5 0 07 Nov 2024
Legitimate ground-truth-free metrics for deep uncertainty classification scoring Arthur Pignet Chiara Regniez John Klein 119 1 0 30 Oct 2024
Are We Done with MMLU? Aryo Pradipta Gema Joshua Ong Jun Leang Giwon Hong Alessio Devoto Alberto Carlo Maria Mancino ... R. McHardy Joshua Harris Jean Kaddour Emile van Krieken Pasquale Minervini ELM 110 39 0 06 Jun 2024
Learning Personalized Decision Support Policies Umang Bhatt Valerie Chen Katherine M. Collins Parameswaran Kamalaruban Emma Kallina Adrian Weller Ameet Talwalkar OffRL 161 11 0 13 Apr 2023
Do CIFAR-10 Classifiers Generalize to CIFAR-10? Benjamin Recht Rebecca Roelofs Ludwig Schmidt Vaishaal Shankar OOD FedML ELM 156 409 0 01 Jun 2018
Robust Loss Functions under Label Noise for Deep Neural Networks Aritra Ghosh Himanshu Kumar P. Sastry NoLa OOD 64 955 0 27 Dec 2017
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning Battista Biggio Fabio Roli AAML 111 1,407 0 08 Dec 2017
Deep Learning Scaling is Predictable, Empirically Joel Hestness Sharan Narang Newsha Ardalani G. Diamos Heewoo Jun Hassan Kianinejad Md. Mostofa Ali Patwary Yang Yang Yanqi Zhou 87 736 0 01 Dec 2017
mixup: Beyond Empirical Risk Minimization Hongyi Zhang Moustapha Cissé Yann N. Dauphin David Lopez-Paz NoLa 271 9,743 0 25 Oct 2017
Toward Robustness against Label Noise in Training Deep Discriminative Neural Networks Arash Vahdat NoLa 75 298 0 31 May 2017
Deep Learning is Robust to Massive Label Noise David Rolnick Andreas Veit Serge J. Belongie Nir Shavit NoLa 70 555 0 30 May 2017
Shake-Shake regularization Xavier Gastaldi 3DPC BDL OOD 76 380 0 21 May 2017
Aggregated Residual Transformations for Deep Neural Networks Saining Xie Ross B. Girshick Piotr Dollár Zhuowen Tu Kaiming He 493 10,305 0 16 Nov 2016
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 461 3,138 0 04 Nov 2016
Deep Pyramidal Residual Networks Dongyoon Han Jiwhan Kim Junmo Kim 93 692 0 10 Oct 2016
Densely Connected Convolutional Networks Gao Huang Zhuang Liu Laurens van der Maaten Kilian Q. Weinberger PINN 3DV 725 36,708 0 25 Aug 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 517 5,893 0 08 Jul 2016
Wide Residual Networks Sergey Zagoruyko N. Komodakis 322 7,971 0 23 May 2016
Identity Mappings in Deep Residual Networks Kaiming He Xinming Zhang Shaoqing Ren Jian Sun 342 10,172 0 16 Mar 2016
Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations Ranjay Krishna Yuke Zhu Oliver Groth Justin Johnson Kenji Hata ... Yannis Kalantidis Li Li David A. Shamma Michael S. Bernstein Fei-Fei Li 196 5,726 0 23 Feb 2016
Embracing Error to Enable Rapid Crowdsourcing Ranjay Krishna Kenji Hata Stephanie Chen Joshua Kravitz David A. Shamma Li Fei-Fei Michael S. Bernstein LRM 74 91 0 14 Feb 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.1K 193,426 0 10 Dec 2015
Rethinking the Inception Architecture for Computer Vision Christian Szegedy Vincent Vanhoucke Sergey Ioffe Jonathon Shlens Z. Wojna 3DV BDL 804 27,303 0 02 Dec 2015
Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks Nicolas Papernot Patrick McDaniel Xi Wu S. Jha A. Swami AAML 80 3,072 0 14 Nov 2015
Distilling the Knowledge in a Neural Network Geoffrey E. Hinton Oriol Vinyals J. Dean FedML 320 19,609 0 09 Mar 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.6K 149,842 0 22 Dec 2014
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 243 19,017 0 20 Dec 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.5K 100,213 0 04 Sep 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 1.6K 39,472 0 01 Sep 2014
Microsoft COCO: Common Objects in Context Nayeon Lee Michael Maire Serge J. Belongie Lubomir Bourdev Ross B. Girshick James Hays Pietro Perona Deva Ramanan C. L. Zitnick Piotr Dollár ObjD 381 43,524 0 01 May 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 249 14,893 1 21 Dec 2013