Using Pre-Training Can Improve Model Robustness and Uncertainty

28 January 2019

Papers citing "Using Pre-Training Can Improve Model Robustness and Uncertainty"

50 / 154 papers shown

Title
LAFEAT: Piercing Through Adversarial Defenses with Latent Features Yunrui Yu Xitong Gao Chengzhong Xu AAML FedML 33 44 0 19 Apr 2021
Contrastive Learning Improves Model Robustness Under Label Noise Aritra Ghosh Andrew S. Lan NoLa 21 58 0 19 Apr 2021
Does Your Dermatology Classifier Know What It Doesn't Know? Detecting the Long-Tail of Unseen Conditions Abhijit Guha Roy Jie Jessie Ren Shekoofeh Azizi Aaron Loh Vivek Natarajan ... Yun-Hui Liu taylan. cemgil Alan Karthikesalingam Balaji Lakshminarayanan Jim Winkens 18 104 0 08 Apr 2021
Adversarial Robustness under Long-Tailed Distribution Tong Wu Ziwei Liu Qingqiu Huang Yu Wang Dahua Lin 21 76 0 06 Apr 2021
On the Adversarial Robustness of Vision Transformers Rulin Shao Zhouxing Shi Jinfeng Yi Pin-Yu Chen Cho-Jui Hsieh ViT 33 137 0 29 Mar 2021
Combating Adversaries with Anti-Adversaries Motasem Alfarra Juan C. Pérez Ali K. Thabet Adel Bibi Philip Torr Guohao Li AAML 34 26 0 26 Mar 2021
StyleLess layer: Improving robustness for real-world driving Julien Rebut Andrei Bursuc P. Pérez 30 5 0 25 Mar 2021
Characterizing and Improving the Robustness of Self-Supervised Learning through Background Augmentations Chaitanya K. Ryali D. Schwab Ari S. Morcos SSL 32 9 0 23 Mar 2021
Towards Evaluating the Robustness of Deep Diagnostic Models by Adversarial Attack Mengting Xu Tao Zhang Zhongnian Li Mingxia Liu Daoqiang Zhang AAML OOD MedIm 33 41 0 05 Mar 2021
Fixing Data Augmentation to Improve Adversarial Robustness Sylvestre-Alvise Rebuffi Sven Gowal D. A. Calian Florian Stimberg Olivia Wiles Timothy A. Mann AAML 36 269 0 02 Mar 2021
On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning Ren Wang Kaidi Xu Sijia Liu Pin-Yu Chen Tsui-Wei Weng Chuang Gan Meng Wang AAML 21 47 0 20 Feb 2021
Guided Interpolation for Adversarial Training Chen Chen Jingfeng Zhang Xilie Xu Tianlei Hu Gang Niu Gang Chen Masashi Sugiyama AAML 30 10 0 15 Feb 2021
Bridging In- and Out-of-distribution Samples for Their Better Discriminability Engkarat Techapanurak Anh-Chuong Dang Takayuki Okatani OODD 25 3 0 07 Jan 2021
Advances in Electron Microscopy with Deep Learning Jeffrey M. Ede 35 2 0 04 Jan 2021
Composite Adversarial Attacks Xiaofeng Mao YueFeng Chen Shuhui Wang Hang Su Yuan He Hui Xue AAML 33 48 0 10 Dec 2020
Multi-Objective Interpolation Training for Robustness to Label Noise Diego Ortego Eric Arazo Paul Albert Noel E. O'Connor Kevin McGuinness NoLa 27 112 0 08 Dec 2020
Data-Dependent Randomized Smoothing Motasem Alfarra Adel Bibi Philip Torr Guohao Li UQCV 23 34 0 08 Dec 2020
Guided Adversarial Attack for Evaluating and Enhancing Adversarial Defenses Gaurang Sriramanan Sravanti Addepalli Arya Baburaj R. Venkatesh Babu AAML 25 92 0 30 Nov 2020
Learnable Boundary Guided Adversarial Training Jiequan Cui Shu Liu Liwei Wang Jiaya Jia OOD AAML 30 124 0 23 Nov 2020
Unsupervised Contrastive Learning of Sound Event Representations Eduardo Fonseca Diego Ortego Kevin McGuinness Noel E. O'Connor Xavier Serra SSL 27 65 0 15 Nov 2020
A Survey of Label-noise Representation Learning: Past, Present and Future Bo Han Quanming Yao Tongliang Liu Gang Niu Ivor W. Tsang James T. Kwok Masashi Sugiyama NoLa 24 158 0 09 Nov 2020
PEP: Parameter Ensembling by Perturbation Alireza Mehrtash Purang Abolmaesumi Polina Golland Tina Kapur Demian Wassermann W. Wells 25 10 0 24 Oct 2020
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 234 678 0 19 Oct 2020
Optimism in the Face of Adversity: Understanding and Improving Deep Learning through Adversarial Robustness Guillermo Ortiz-Jiménez Apostolos Modas Seyed-Mohsen Moosavi-Dezfooli P. Frossard AAML 29 48 0 19 Oct 2020
PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation Tal Reiss Niv Cohen Liron Bergman Yedid Hoshen 16 247 0 12 Oct 2020
Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples Sven Gowal Chongli Qin J. Uesato Timothy A. Mann Pushmeet Kohli AAML 17 324 0 07 Oct 2020
Deep Anomaly Detection by Residual Adaptation Lucas Deecke Lukas Ruff Robert A. Vandermeulen Hakan Bilen UQCV 28 4 0 05 Oct 2020
Geometry-aware Instance-reweighted Adversarial Training Jingfeng Zhang Jianing Zhu Gang Niu Bo Han Masashi Sugiyama Mohan Kankanhalli AAML 47 269 0 05 Oct 2020
Adversarial Training with Stochastic Weight Average Joong-won Hwang Youngwan Lee Sungchan Oh Yuseok Bae OOD AAML 29 11 0 21 Sep 2020
TRIER: Template-Guided Neural Networks for Robust and Interpretable Sleep Stage Identification from EEG Recordings Taeheon Lee Jeonghwan Hwang Honggu Lee 35 7 0 10 Sep 2020
A Primer on Motion Capture with Deep Learning: Principles, Pitfalls and Perspectives Alexander Mathis Steffen Schneider Jessy Lauer Mackenzie W. Mathis 35 165 0 01 Sep 2020
Stylized Adversarial Defense Muzammal Naseer Salman Khan Munawar Hayat Fahad Shahbaz Khan Fatih Porikli GAN AAML 28 16 0 29 Jul 2020
CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances Jihoon Tack Sangwoo Mo Jongheon Jeong Jinwoo Shin OODD 11 588 0 16 Jul 2020
An Empirical Study on Robustness to Spurious Correlations using Pre-trained Language Models Lifu Tu Garima Lalwani Spandana Gella He He LRM 24 184 0 14 Jul 2020
How benign is benign overfitting? Amartya Sanyal P. Dokania Varun Kanade Philip Torr NoLa AAML 23 57 0 08 Jul 2020
Knowledge Distillation Beyond Model Compression F. Sarfraz Elahe Arani Bahram Zonooz 12 40 0 03 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 110 1,672 0 29 Jun 2020
Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness Jeremiah Zhe Liu Zi Lin Shreyas Padhy Dustin Tran Tania Bedrax-Weiss Balaji Lakshminarayanan UQCV BDL 37 437 0 17 Jun 2020
On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them Chen Liu Mathieu Salzmann Tao R. Lin Ryota Tomioka Sabine Süsstrunk AAML 24 81 0 15 Jun 2020
Adversarial Self-Supervised Contrastive Learning Minseon Kim Jihoon Tack Sung Ju Hwang SSL 28 246 0 13 Jun 2020
Large-Scale Adversarial Training for Vision-and-Language Representation Learning Zhe Gan Yen-Chun Chen Linjie Li Chen Zhu Yu Cheng Jingjing Liu ObjD VLM 35 488 0 11 Jun 2020
Multi-Stage Conversational Passage Retrieval: An Approach to Fusing Term Importance Estimation and Neural Query Rewriting Sheng-Chieh Lin Jheng-Hong Yang Rodrigo Nogueira Ming-Feng Tsai Chuan-Ju Wang Jimmy J. Lin 19 24 0 05 May 2020
On Calibration of Mixup Training for Deep Neural Networks Juan Maroñas D. Ramos-Castro Roberto Paredes Palacios UQCV 30 6 0 22 Mar 2020
Adversarial Robustness on In- and Out-Distribution Improves Explainability Maximilian Augustin Alexander Meinke Matthias Hein OOD 75 98 0 20 Mar 2020
A comprehensive study on the prediction reliability of graph neural networks for virtual screening Soojung Yang K. Lee Seongok Ryu 19 7 0 17 Mar 2020
Efficient Adversarial Training with Transferable Adversarial Examples Haizhong Zheng Ziqi Zhang Juncheng Gu Honglak Lee A. Prakash AAML 24 108 0 27 Dec 2019
Robust Training with Ensemble Consensus Jisoo Lee Sae-Young Chung NoLa 22 28 0 22 Oct 2019
Pretraining boosts out-of-domain robustness for pose estimation Alexander Mathis Thomas Biasi Steffen Schneider Mert Yüksekgönül Byron Rogers Matthias Bethge Mackenzie W. Mathis OOD 30 122 0 24 Sep 2019
Verified Uncertainty Calibration Ananya Kumar Percy Liang Tengyu Ma 24 346 0 23 Sep 2019
Intriguing properties of adversarial training at scale Cihang Xie Alan Yuille AAML 13 68 0 10 Jun 2019