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DC4L: Distribution Shift Recovery via Data-Driven Control for Deep Learning Models

20 February 2023

Papers citing "DC4L: Distribution Shift Recovery via Data-Driven Control for Deep Learning Models"

32 / 32 papers shown

Title
Conformalized Credal Regions for Classification with Ambiguous Ground Truth Michele Caprio David Stutz Shuo Li Arnaud Doucet UQCV 210 5 0 07 Nov 2024
Imprecise Markov Semigroups and their Ergodicity Michele Caprio 72 3 0 30 Apr 2024
Test-Time Training with Masked Autoencoders Yossi Gandelsman Yu Sun Xinlei Chen Alexei A. Efros OOD 101 177 0 15 Sep 2022
Agreement-on-the-Line: Predicting the Performance of Neural Networks under Distribution Shift Christina Baek Yiding Jiang Aditi Raghunathan Zico Kolter 92 87 0 27 Jun 2022
Learning Enriched Features for Fast Image Restoration and Enhancement Syed Waqas Zamir Aditya Arora Salman Khan Munawar Hayat Fahad Shahbaz Khan Ming-Hsuan Yang Ling Shao SupR 69 412 0 19 Apr 2022
Continual Test-Time Domain Adaptation Qin Wang Olga Fink Luc Van Gool Dengxin Dai OOD TTA 109 431 0 25 Mar 2022
Deep Image Deblurring: A Survey Kaihao Zhang Wenqi Ren Wenhan Luo Wei-Sheng Lai B. Stenger Ming-Hsuan Yang Hongdong Li 166 244 0 26 Jan 2022
Accuracy on the Line: On the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization John Miller Rohan Taori Aditi Raghunathan Shiori Sagawa Pang Wei Koh Vaishaal Shankar Percy Liang Y. Carmon Ludwig Schmidt OODD OOD 94 278 0 09 Jul 2021
Test-Time Adaptation to Distribution Shift by Confidence Maximization and Input Transformation Chaithanya Kumar Mummadi Robin Hutmacher K. Rambach Evgeny Levinkov Thomas Brox J. H. Metzen TTA OOD 159 70 0 28 Jun 2021
Multi-Stage Progressive Image Restoration Syed Waqas Zamir Aditya Arora Salman Khan Munawar Hayat Fahad Shahbaz Khan Ming-Hsuan Yang Ling Shao 179 1,493 0 04 Feb 2021
Why do classifier accuracies show linear trends under distribution shift? Horia Mania S. Sra OOD 85 20 0 31 Dec 2020
Distances between probability distributions of different dimensions Yuhan Cai Lek-Heng Lim UD OOD 71 50 0 01 Nov 2020
Learning Loss for Test-Time Augmentation Ildoo Kim Younghoon Kim Sungwoong Kim OOD 72 92 0 22 Oct 2020
Puzzle Mix: Exploiting Saliency and Local Statistics for Optimal Mixup Jang-Hyun Kim Wonho Choo Hyun Oh Song AAML 91 390 0 15 Sep 2020
The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalization Dan Hendrycks Steven Basart Norman Mu Saurav Kadavath Frank Wang ... Samyak Parajuli Mike Guo Basel Alomair Jacob Steinhardt Justin Gilmer OOD 350 1,754 0 29 Jun 2020
Learning Enriched Features for Real Image Restoration and Enhancement Syed Waqas Zamir Aditya Arora Salman Khan Munawar Hayat Fahad Shahbaz Khan Ming-Hsuan Yang Ling Shao SupR 70 615 0 15 Mar 2020
Greedy Policy Search: A Simple Baseline for Learnable Test-Time Augmentation Dmitry Molchanov Alexander Lyzhov Yuliya Molchanova Arsenii Ashukha Dmitry Vetrov TPM 99 85 0 21 Feb 2020
AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty Dan Hendrycks Norman Mu E. D. Cubuk Barret Zoph Justin Gilmer Balaji Lakshminarayanan OOD UQCV 125 1,307 0 05 Dec 2019
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features Sangdoo Yun Dongyoon Han Seong Joon Oh Sanghyuk Chun Junsuk Choe Y. Yoo OOD 622 4,802 0 13 May 2019
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations Dan Hendrycks Thomas G. Dietterich OOD VLM 191 3,452 0 28 Mar 2019
Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift Stephan Rabanser Stephan Günnemann Zachary Chase Lipton 61 370 0 29 Oct 2018
Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples Kimin Lee Honglak Lee Kibok Lee Jinwoo Shin OODD 120 882 0 26 Nov 2017
CyCADA: Cycle-Consistent Adversarial Domain Adaptation Judy Hoffman Eric Tzeng Taesung Park Jun-Yan Zhu Phillip Isola Kate Saenko Alexei A. Efros Trevor Darrell 147 3,005 0 08 Nov 2017
Countering Adversarial Images using Input Transformations Chuan Guo Mayank Rana Moustapha Cissé Laurens van der Maaten AAML 125 1,406 0 31 Oct 2017
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks Dan Hendrycks Kevin Gimpel UQCV 171 3,472 0 07 Oct 2016
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network C. Ledig Lucas Theis Ferenc Huszár Jose Caballero Andrew Cunningham ... Andrew P. Aitken Alykhan Tejani J. Totz Zehan Wang Wenzhe Shi GAN 242 10,712 0 15 Sep 2016
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising Peng Sun W. Zuo Yunjin Chen Deyu Meng Lei Zhang SupR 145 7,012 0 13 Aug 2016
Wide Residual Networks Sergey Zagoruyko N. Komodakis 353 8,000 0 23 May 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 194,426 0 10 Dec 2015
On Wasserstein Two Sample Testing and Related Families of Nonparametric Tests Aaditya Ramdas Nicolas García Trillos Marco Cuturi 71 486 0 08 Sep 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 282 19,121 0 20 Dec 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.7K 100,508 0 04 Sep 2014