Models Out of Line: A Fourier Lens on Distribution Shift Robustness

8 July 2022

Papers citing "Models Out of Line: A Fourier Lens on Distribution Shift Robustness"

44 / 44 papers shown

Title
Certified Adversarial Defenses Meet Out-of-Distribution Corruptions: Benchmarking Robustness and Simple Baselines Jiachen Sun Akshay Mehra B. Kailkhura Pin-Yu Chen Dan Hendrycks Jihun Hamm Z. Morley Mao AAML 53 22 0 01 Dec 2021
Spectral Bias in Practice: The Role of Function Frequency in Generalization Sara Fridovich-Keil Raphael Gontijo-Lopes Rebecca Roelofs 59 30 0 06 Oct 2021
Robust fine-tuning of zero-shot models Mitchell Wortsman Gabriel Ilharco Jong Wook Kim Mike Li Simon Kornblith ... Raphael Gontijo-Lopes Hannaneh Hajishirzi Ali Farhadi Hongseok Namkoong Ludwig Schmidt VLM 114 721 0 04 Sep 2021
Amplitude-Phase Recombination: Rethinking Robustness of Convolutional Neural Networks in Frequency Domain Guangyao Chen Peixi Peng Li Ma Jia Li Lin Du Yonghong Tian AAML OOD 54 95 0 19 Aug 2021
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 56 274 0 09 Jul 2021
Predicting with Confidence on Unseen Distributions Devin Guillory Vaishaal Shankar Sayna Ebrahimi Trevor Darrell Ludwig Schmidt UQCV OOD 48 120 0 07 Jul 2021
The Evolution of Out-of-Distribution Robustness Throughout Fine-Tuning Anders Andreassen Yasaman Bahri Behnam Neyshabur Rebecca Roelofs OOD OODD 63 81 0 30 Jun 2021
Multi-Prize Lottery Ticket Hypothesis: Finding Accurate Binary Neural Networks by Pruning A Randomly Weighted Network James Diffenderfer B. Kailkhura MQ 47 75 0 17 Mar 2021
On the effectiveness of adversarial training against common corruptions Klim Kireev Maksym Andriushchenko Nicolas Flammarion AAML 56 103 0 03 Mar 2021
Learning Transferable Visual Models From Natural Language Supervision Alec Radford Jong Wook Kim Chris Hallacy Aditya A. Ramesh Gabriel Goh ... Amanda Askell Pamela Mishkin Jack Clark Gretchen Krueger Ilya Sutskever CLIP VLM 808 29,167 0 26 Feb 2021
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 302 700 0 19 Oct 2020
On Robustness and Transferability of Convolutional Neural Networks Josip Djolonga Jessica Yung Michael Tschannen Rob Romijnders Lucas Beyer ... D. Moldovan Sylvain Gelly N. Houlsby Xiaohua Zhai Mario Lucic OOD 52 154 0 16 Jul 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 D. Song Jacob Steinhardt Justin Gilmer OOD 298 1,727 0 29 Jun 2020
Comparing Rewinding and Fine-tuning in Neural Network Pruning Alex Renda Jonathan Frankle Michael Carbin 258 387 0 05 Mar 2020
Hold me tight! Influence of discriminative features on deep network boundaries Guillermo Ortiz-Jiménez Apostolos Modas Seyed-Mohsen Moosavi-Dezfooli P. Frossard AAML 32 50 0 15 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 97 1,299 0 05 Dec 2019
Fantastic Generalization Measures and Where to Find Them Yiding Jiang Behnam Neyshabur H. Mobahi Dilip Krishnan Samy Bengio AI4CE 107 606 0 04 Dec 2019
What's Hidden in a Randomly Weighted Neural Network? Vivek Ramanujan Mitchell Wortsman Aniruddha Kembhavi Ali Farhadi Mohammad Rastegari 66 356 0 29 Nov 2019
What Do Compressed Deep Neural Networks Forget? Sara Hooker Aaron Courville Gregory Clark Yann N. Dauphin Andrea Frome 75 184 0 13 Nov 2019
Robust Learning with Jacobian Regularization Judy Hoffman Daniel A. Roberts Sho Yaida OOD AAML 48 167 0 07 Aug 2019
A Fourier Perspective on Model Robustness in Computer Vision Dong Yin Raphael Gontijo-Lopes Jonathon Shlens E. D. Cubuk Justin Gilmer OOD 79 496 0 21 Jun 2019
Do Image Classifiers Generalize Across Time? Vaishaal Shankar Achal Dave Rebecca Roelofs Deva Ramanan Benjamin Recht Ludwig Schmidt 117 83 0 05 Jun 2019
The Convergence Rate of Neural Networks for Learned Functions of Different Frequencies Ronen Basri David Jacobs Yoni Kasten S. Kritchman 64 217 0 02 Jun 2019
Learning Robust Global Representations by Penalizing Local Predictive Power Haohan Wang Songwei Ge Eric Xing Zachary Chase Lipton OOD 104 955 0 29 May 2019
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations Dan Hendrycks Thomas G. Dietterich OOD VLM 144 3,423 0 28 Mar 2019
Do ImageNet Classifiers Generalize to ImageNet? Benjamin Recht Rebecca Roelofs Ludwig Schmidt Vaishaal Shankar OOD SSeg VLM 103 1,709 0 13 Feb 2019
ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness Robert Geirhos Patricia Rubisch Claudio Michaelis Matthias Bethge Felix Wichmann Wieland Brendel 96 2,662 0 29 Nov 2018
MnasNet: Platform-Aware Neural Architecture Search for Mobile Mingxing Tan Bo Chen Ruoming Pang Vijay Vasudevan Mark Sandler Andrew G. Howard Quoc V. Le MQ 114 3,004 0 31 Jul 2018
ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design Ningning Ma Xiangyu Zhang Haitao Zheng Jian Sun 150 4,970 0 30 Jul 2018
Training behavior of deep neural network in frequency domain Zhi-Qin John Xu Yaoyu Zhang Yan Xiao AI4CE 61 319 0 03 Jul 2018
On the Spectral Bias of Neural Networks Nasim Rahaman A. Baratin Devansh Arpit Felix Dräxler Min Lin Fred Hamprecht Yoshua Bengio Aaron Courville 120 1,432 0 22 Jun 2018
Do CIFAR-10 Classifiers Generalize to CIFAR-10? Benjamin Recht Rebecca Roelofs Ludwig Schmidt Vaishaal Shankar OOD FedML ELM 139 409 0 01 Jun 2018
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks Jonathan Frankle Michael Carbin 202 3,457 0 09 Mar 2018
MobileNetV2: Inverted Residuals and Linear Bottlenecks Mark Sandler Andrew G. Howard Menglong Zhu A. Zhmoginov Liang-Chieh Chen 169 19,204 0 13 Jan 2018
To prune, or not to prune: exploring the efficacy of pruning for model compression Michael Zhu Suyog Gupta 169 1,273 0 05 Oct 2017
Aggregated Residual Transformations for Deep Neural Networks Saining Xie Ross B. Girshick Piotr Dollár Zhuowen Tu Kaiming He 476 10,305 0 16 Nov 2016
Densely Connected Convolutional Networks Gao Huang Zhuang Liu Laurens van der Maaten Kilian Q. Weinberger PINN 3DV 713 36,708 0 25 Aug 2016
Wide Residual Networks Sergey Zagoruyko N. Komodakis 308 7,971 0 23 May 2016
SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size F. Iandola Song Han Matthew W. Moskewicz Khalid Ashraf W. Dally Kurt Keutzer 139 7,465 0 24 Feb 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 1.9K 193,426 0 10 Dec 2015
Learning both Weights and Connections for Efficient Neural Networks Song Han Jeff Pool J. Tran W. Dally CVBM 283 6,660 0 08 Jun 2015
Going Deeper with Convolutions Christian Szegedy Wei Liu Yangqing Jia P. Sermanet Scott E. Reed Dragomir Anguelov D. Erhan Vincent Vanhoucke Andrew Rabinovich 399 43,589 0 17 Sep 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.3K 100,213 0 04 Sep 2014
One weird trick for parallelizing convolutional neural networks A. Krizhevsky GNN 88 1,298 0 23 Apr 2014