Fetching the paper…
Reading the bibliography…
As machine learning models continue to achieve impressive performance across different tasks, the importance of effective anomaly detection for such models has increased as well.
On the generalised distance in statistics
Prasanta Chandra Mahalanobis · 1936
Earlier work this paper cites.
Gradient-based learning applied to document recognition
Yann LeCun, Léon Bottou, Yoshua Bengio, and Patrick Haffner · 1998
Earlier work this paper cites.
Shape context: A new descriptor for shape matching and object recognition
Serge Belongie, Jitendra Malik, and Jan Puzicha · 2000
Earlier work this paper cites.
Image Quality Assessment: From Error Visibility to Structural Similarity
Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli · 2003
Earlier work this paper cites.
Efficient graph-based image segmentation
Pedro F Felzenszwalb and Daniel P Huttenlocher · 2004
Earlier work this paper cites.
Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
Earlier work this paper cites.
On the mathematical properties of the structural similarity index
Dominique Brunet, Edward R. Vrscay, and Zhou Wang · 2011
Earlier work this paper cites.
Reading digits in natural images with unsupervised feature learning
Yuval Netzer, Tao Wang, Adam Coates, Alessandro Bissacco, Bo Wu, and Andrew Y Ng · 2011
Earlier work this paper cites.
Deep speech: Scaling up end-to-end speech recognition
Awni Hannun, Carl Case, Jared Casper, Bryan Catanzaro, Greg Diamos, Erich Elsen, Ryan Prenger, Sanjeev Satheesh, Shubho Sengupta, Adam Coates, et al · 2014
Earlier work this paper cites.
Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
Earlier work this paper cites.
Unsupervised domain adaptation by backpropagation
Yaroslav Ganin and Victor Lempitsky · 2015
Earlier work this paper cites.
Contextual action recognition with r* cnn
Georgia Gkioxari, Ross Girshick, and Jitendra Malik · 2015
Earlier work this paper cites.
Deep learning face attributes in the wild
Ziwei Liu, Ping Luo, Xiaogang Wang, and Xiaoou Tang · 2015
Earlier work this paper cites.
Lsun: Construction of a large-scale image dataset using deep learning with humans in the loop
Fisher Yu, Ari Seff, Yinda Zhang, Shuran Song, Thomas Funkhouser, and Jianxiong Xiao · 2015
Earlier work this paper cites.
End to end learning for self-driving cars
Mariusz Bojarski, Davide Del Testa, Daniel Dworakowski, Bernhard Firner, Beat Flepp, Prasoon Goyal, Lawrence D Jackel, Mathew Monfort, Urs Muller, Jiakai Zhang, et al · 2016
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Cited alongside, same era.
A baseline for detecting misclassified and out-of-distribution examples in neural networks
Dan Hendrycks and Kevin Gimpel · 2016
Cited alongside, same era.
Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs
Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, and Alan L Yuille · 2017
Cited alongside, same era.
A review on deep learning techniques applied to semantic segmentation
Alberto Garcia-Garcia, Sergio Orts-Escolano, Sergiu Oprea, Victor Villena-Martinez, and Jose Garcia-Rodriguez · 2017
Cited alongside, same era.
Enhancing the reliability of out-of-distribution image detection in neural networks
Maskgan: Towards diverse and interactive facial image manipulation
Cheng-Han Lee, Ziwei Liu, Lingyun Wu, and Ping Luo · 2020
Later among the works it cites.
Energy-based out-of-distribution detection
Weitang Liu, Xiaoyun Wang, John Owens, and Yixuan Li · 2020
Later among the works it cites.
Detecting out-of-distribution examples with gram matrices
Chandramouli Shama Sastry and Sageev Oore · 2020
Later among the works it cites.
Learning to generate novel domains for domain generalization
Kaiyang Zhou, Yongxin Yang, Timothy Hospedales, and Tao Xiang · 2020
Later among the works it cites.
Exploiting domain-specific features to enhance domain generalization
Manh-Ha Bui, Toan Tran, Anh Tran, and Dinh Phung · 2021
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Shiyu Liang, Yixuan Li, and Rayadurgam Srikant · 2017
Cited alongside, same era.
Feature pyramid networks for object detection
Tsung-Yi Lin, Piotr Dollár, Ross Girshick, Kaiming He, Bharath Hariharan, and Serge Belongie · 2017
Cited alongside, same era.
Deep learning-based document modeling for personality detection from text
Navonil Majumder, Soujanya Poria, Alexander Gelbukh, and Erik Cambria · 2017
Cited alongside, same era.
Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms
Han Xiao, Kashif Rasul, and Roland Vollgraf · 2017
Cited alongside, same era.
Clinically applicable deep learning for diagnosis and referral in retinal disease
Jeffrey De Fauw, Joseph R Ledsam, Bernardino Romera-Paredes, Stanislav Nikolov, Nenad Tomasev, Sam Blackwell, Harry Askham, Xavier Glorot, Brendan O’Donoghue, Daniel Visentin, et al · 2018
Cited alongside, same era.
A simple unified framework for detecting out-of-distribution samples and adversarial attacks
Kimin Lee, Kibok Lee, Honglak Lee, and Jinwoo Shin · 2018
Cited alongside, same era.
Deep domain generalization via conditional invariant adversarial networks
Ya Li, Xinmei Tian, Mingming Gong, Yajing Liu, Tongliang Liu, Kun Zhang, and Dacheng Tao · 2018
Cited alongside, same era.
Using self-supervised learning can improve model robustness and uncertainty
Dan Hendrycks, Mantas Mazeika, Saurav Kadavath, and Dawn Song · 2019
Cited alongside, same era.
Nooshin Mojab, Philip S Yu, Joelle A Hallak, and Darvin Yi · 2021
Later among the works it cites.
Memory classifiers: Two-stage classification for robustness in machine learning
Souradeep Dutta, Yahan Yang, Elena Bernardis, Edgar Dobriban, and Insup Lee · 2022
Later among the works it cites.
Category-stitch learning for union domain generalization
Yajing Liu, Zhiwei Xiong, Ya Li, Yuning Lu, Xinmei Tian, and Zheng-Jun Zha · 2022
Later among the works it cites.
On the impact of spurious correlation for out-of-distribution detection
Yifei Ming, Hang Yin, and Yixuan Li · 2022
Later among the works it cites.
Review the state-of-the-art technologies of semantic segmentation based on deep learning
Yujian Mo, Yan Wu, Xinneng Yang, Feilin Liu, and Yujun Liao · 2022
Later among the works it cites.
Meta convolutional neural networks for single domain generalization
Chaoqun Wan, Xu Shen, Yonggang Zhang, Zhiheng Yin, Xinmei Tian, Feng Gao, Jianqiang Huang, and Xian-Sheng Hua · 2022
Later among the works it cites.
Contrastive learning rivals masked image modeling in fine-tuning via feature distillation
Yixuan Wei, Han Hu, Zhenda Xie, Zheng Zhang, Yue Cao, Jianmin Bao, Dong Chen, and Baining Guo · 2022
Later among the works it cites.
Interpretable detection of distribution shifts in learning enabled cyber-physical systems
Yahan Yang, Ramneet Kaur, Souradeep Dutta, and Insup Lee · 2022
Later among the works it cites.
Domain generalization: A survey
Kaiyang Zhou, Ziwei Liu, Yu Qiao, Tao Xiang, and Chen Change Loy · 2022
Later among the works it cites.