Robustness of Conditional GANs to Noisy Labels

8 November 2018

Papers citing "Robustness of Conditional GANs to Noisy Labels"

50 / 56 papers shown

Title
Slight Corruption in Pre-training Data Makes Better Diffusion Models Hao Chen Yujin Han Diganta Misra Xiang Li Kai Hu Difan Zou Masashi Sugiyama Jindong Wang Bhiksha Raj DiffM 47 5 0 30 May 2024
Label-Noise Robust Diffusion Models Byeonghu Na Yeongmin Kim Heesun Bae Jung Hyun Lee Seho Kwon Wanmo Kang Il-Chul Moon NoLa DiffM 50 8 0 27 Feb 2024
Fusing Conditional Submodular GAN and Programmatic Weak Supervision Kumar Shubham Pranav Sastry AP Prathosh 21 1 0 16 Dec 2023
On Measuring Fairness in Generative Models Christopher T. H. Teo Milad Abdollahzadeh Ngai-man Cheung EGVM 22 5 0 30 Oct 2023
Soft Curriculum for Learning Conditional GANs with Noisy-Labeled and Uncurated Unlabeled Data Kai Katsumata D. Vo Tatsuya Harada Hideki Nakayama 31 0 0 17 Jul 2023
Near Optimal Private and Robust Linear Regression Xiyang Liu Prateek Jain Weihao Kong Sewoong Oh A. Suggala 38 9 0 30 Jan 2023
PADDLES: Phase-Amplitude Spectrum Disentangled Early Stopping for Learning with Noisy Labels Huaxi Huang Hui-Sung Kang Sheng Liu Olivier Salvado Thierry Rakotoarivelo Dadong Wang Tongliang Liu NoLa 25 7 0 07 Dec 2022
Establishment of Neural Networks Robust to Label Noise Pengwei Yang Angel Teng Jack Mangos NoLa 14 0 0 28 Nov 2022
Dynamic-Pix2Pix: Noise Injected cGAN for Modeling Input and Target Domain Joint Distributions with Limited Training Data Mohammadreza Naderi N. Karimi Ali Emami S. Shirani S. Samavi 18 0 0 15 Nov 2022
Tackling Instance-Dependent Label Noise with Dynamic Distribution Calibration Manyi Zhang Yuxin Ren Zihao W. Wang C. Yuan 21 3 0 11 Oct 2022
Learning to segment fetal brain tissue from noisy annotations Davood Karimi C. Rollins C. Velasco-Annis Abdelhakim Ouaalam Ali Gholipour 18 25 0 25 Mar 2022
Generative Modeling Helps Weak Supervision (and Vice Versa) Benedikt Boecking Nicholas Roberts W. Neiswanger Stefano Ermon Frederic Sala Artur Dubrawski 23 1 0 22 Mar 2022
Do We Need to Penalize Variance of Losses for Learning with Label Noise? Yexiong Lin Yu Yao Yuxuan Du Jun Yu Bo Han Mingming Gong Tongliang Liu NoLa 41 3 0 30 Jan 2022
Improved Input Reprogramming for GAN Conditioning Tuan Dinh Daewon Seo Zhixu Du Liang Shang Kangwook Lee AI4CE 22 8 0 07 Jan 2022
Learning with Noisy Labels by Efficient Transition Matrix Estimation to Combat Label Miscorrection Seong Min Kye Kwanghee Choi Joonyoung Yi Buru Chang NoLa 31 15 0 29 Nov 2021
Dual Projection Generative Adversarial Networks for Conditional Image Generation Ligong Han Martin Renqiang Min Anastasis Stathopoulos Yu Tian Ruijiang Gao Asim Kadav Dimitris N. Metaxas GAN 33 21 0 20 Aug 2021
Sample Selection with Uncertainty of Losses for Learning with Noisy Labels Xiaobo Xia Tongliang Liu Bo Han Mingming Gong Jun Yu Gang Niu Masashi Sugiyama NoLa 15 110 0 01 Jun 2021
Estimating Instance-dependent Bayes-label Transition Matrix using a Deep Neural Network Shuo Yang Erkun Yang Bo Han Yang Liu Min Xu Gang Niu Tongliang Liu NoLa BDL 24 42 0 27 May 2021
Regularizing Generative Adversarial Networks under Limited Data Hung-Yu Tseng Lu Jiang Ce Liu Ming-Hsuan Yang Weilong Yang GAN 22 142 0 07 Apr 2021
Provably End-to-end Label-Noise Learning without Anchor Points Xuefeng Li Tongliang Liu Bo Han Gang Niu Masashi Sugiyama NoLa 124 120 0 04 Feb 2021
Video Summarization Using Deep Neural Networks: A Survey Evlampios Apostolidis E. Adamantidou Alexandros I. Metsai Vasileios Mezaris Ioannis Patras AI4TS 62 201 0 15 Jan 2021
A Survey on Neural Network Interpretability Yu Zhang Peter Tiño A. Leonardis K. Tang FaML XAI 141 660 0 28 Dec 2020
Semantically Robust Unpaired Image Translation for Data with Unmatched Semantics Statistics Zhiwei Jia Bodi Yuan Kangkang Wang Hong Wu David Clifford Zhiqiang Yuan Hao Su VLM 36 21 0 09 Dec 2020
End-to-End Learning from Noisy Crowd to Supervised Machine Learning Models Taraneh Younesian Chi Hong Amirmasoud Ghiassi Robert Birke L. Chen NoLa FedML 8 3 0 13 Nov 2020
Identifying Mislabeled Images in Supervised Learning Utilizing Autoencoder Yunhao Yang Andrew Whinston 16 5 0 07 Nov 2020
GANs for learning from very high class conditional noisy labels Sandhya Tripathi N. Hemachandra GAN 6 1 0 19 Oct 2020
$Beyond $\mathcal{H}$-Divergence: Domain Adaptation Theory With Jensen-Shannon Divergence$ Beyond $\mathcal{H}$ -Divergence: Domain Adaptation Theory With Jensen-Shannon Divergence Changjian Shui Qi Chen Jun Wen Fan Zhou Christian Gagné Boyu Wang 35 22 0 30 Jul 2020
TrustNet: Learning from Trusted Data Against (A)symmetric Label Noise Amirmasoud Ghiassi Taraneh Younesian Robert Birke L. Chen NoLa 16 5 0 13 Jul 2020
ExpertNet: Adversarial Learning and Recovery Against Noisy Labels Amirmasoud Ghiassi Robert Birke Rui Han L. Chen NoLa 14 2 0 10 Jul 2020
A Le Cam Type Bound for Adversarial Learning and Applications Qiuling Xu Kevin Bello Jean Honorio AAML 16 1 0 01 Jul 2020
Classify and Generate Reciprocally: Simultaneous Positive-Unlabelled Learning and Conditional Generation with Extra Data Bin-Xia Yu Ke Sun He-Nan Wang Zhouchen Lin Zhanxing Zhu 9 0 0 14 Jun 2020
Part-dependent Label Noise: Towards Instance-dependent Label Noise Xiaobo Xia Tongliang Liu Bo Han Nannan Wang Mingming Gong Haifeng Liu Gang Niu Dacheng Tao Masashi Sugiyama NoLa 11 67 0 14 Jun 2020
Multi-Level Generative Models for Partial Label Learning with Non-random Label Noise Yan Yan Yuhong Guo 6 13 0 11 May 2020
Robust Generative Adversarial Network Shufei Zhang Zhuang Qian Kaizhu Huang Jimin Xiao Yuan He 14 8 0 28 Apr 2020
Blur, Noise, and Compression Robust Generative Adversarial Networks Takuhiro Kaneko Tatsuya Harada 10 17 0 17 Mar 2020
A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications Jie Gui Zhenan Sun Yonggang Wen Dacheng Tao Jieping Ye EGVM 26 817 0 20 Jan 2020
Generative Pseudo-label Refinement for Unsupervised Domain Adaptation Pietro Morerio Riccardo Volpi R. Ragonesi Vittorio Murino 8 47 0 09 Jan 2020
Image Classification with Deep Learning in the Presence of Noisy Labels: A Survey G. Algan ilkay Ulusoy NoLa VLM 19 322 0 11 Dec 2019
Deep learning with noisy labels: exploring techniques and remedies in medical image analysis Davood Karimi Haoran Dou Simon K. Warfield Ali Gholipour NoLa 11 534 0 05 Dec 2019
Noise Robust Generative Adversarial Networks Takuhiro Kaneko Tatsuya Harada NoLa OOD 22 30 0 26 Nov 2019
Robust Conditional GAN from Uncertainty-Aware Pairwise Comparisons Ligong Han Ruijiang Gao Mun Kim Xin Tao Bo Liu Dimitris N. Metaxas 14 14 0 21 Nov 2019
RAD: On-line Anomaly Detection for Highly Unreliable Data Zilong Zhao Robert Birke Rui Han Bogdan Robu S. Bouchenak Sonia Ben Mokhtar L. Chen AAML 9 6 0 11 Nov 2019
Using GANs for Sharing Networked Time Series Data: Challenges, Initial Promise, and Open Questions Zinan Lin Alankar Jain Chen Wang Giulia Fanti Vyas Sekar 17 22 0 30 Sep 2019
Adversarial Partial Multi-Label Learning Yan Yan Yuhong Guo GAN 14 17 0 15 Sep 2019
Twin Auxiliary Classifiers GAN Mingming Gong Yanwu Xu Chunyuan Li Kuncai Zhang Kayhan Batmanghelich 16 33 0 05 Jul 2019
Robust conditional GANs under missing or uncertain labels K. K. Thekumparampil Sewoong Oh A. Khetan OOD GAN 17 5 0 09 Jun 2019
A Generative Framework for Zero-Shot Learning with Adversarial Domain Adaptation V. Khare Divyat Mahajan Homanga Bharadhwaj Vinay K. Verma Piyush Rai VLM 20 16 0 07 Jun 2019
Are Anchor Points Really Indispensable in Label-Noise Learning? Xiaobo Xia Tongliang Liu N. Wang Bo Han Chen Gong Gang Niu Masashi Sugiyama NoLa 11 369 0 01 Jun 2019
Characterizing Bias in Classifiers using Generative Models Daniel J. McDuff Shuang Ma Yale Song Ashish Kapoor 23 47 0 30 May 2019
Label-Noise Robust Multi-Domain Image-to-Image Translation Takuhiro Kaneko Tatsuya Harada 22 3 0 06 May 2019