Fetching the paper…
Reading the bibliography…
Domain generalization (DG) aims to help models trained on a set of source domains generalize better on unseen target domains.
Extracting and composing robust features with denoising autoencoders
Pascal Vincent, Hugo Larochelle, Yoshua Bengio, and Pierre-Antoine Manzagol · 2008
Earlier work this paper cites.
Learning multiple layers of features from tiny images
Alex Krizhevsky, Geoffrey Hinton, et al · 2009
Earlier work this paper cites.
Unbiased look at dataset bias
Antonio Torralba and Alexei A Efros · 2011
Earlier work this paper cites.
Undoing the damage of dataset bias
Aditya Khosla, Tinghui Zhou, Tomasz Malisiewicz, Alexei A Efros, and Antonio Torralba · 2012
Earlier work this paper cites.
Domain generalization via invariant feature representation
Krikamol Muandet, David Balduzzi, and Bernhard Schölkopf · 2013
Earlier work this paper cites.
Discriminative unsupervised feature learning with convolutional neural networks
Alexey Dosovitskiy, Jost Tobias Springenberg, Martin Riedmiller, and Thomas Brox · 2014
Earlier work this paper cites.
Generative adversarial networks
Ian J Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
Earlier work this paper cites.
Unsupervised visual representation learning by context prediction
Carl Doersch, Abhinav Gupta, and Alexei A Efros · 2015
Earlier work this paper cites.
Domain generalization for object recognition with multi-task autoencoders
Muhammad Ghifary, W Bastiaan Kleijn, Mengjie Zhang, and David Balduzzi · 2015
Earlier work this paper cites.
Jeff Donahue, Philipp Krähenbühl, and Trevor Darrell · 2016
Earlier work this paper cites.
Adversarially learned inference
Vincent Dumoulin, Ishmael Belghazi, Ben Poole, Olivier Mastropietro, Alex Lamb, Martin Arjovsky, and Aaron Courville · 2016
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Unsupervised learning of visual representations by solving jigsaw puzzles
Mehdi Noroozi and Paolo Favaro · 2016
Earlier work this paper cites.
Smart mining for deep metric learning
Ben Harwood, Vijay Kumar BG, Gustavo Carneiro, Ian Reid, and Tom Drummond · 2017
Earlier work this paper cites.
Deeper, broader and artier domain generalization
Da Li, Yongxin Yang, Yi-Zhe Song, and Timothy M Hospedales · 2017
Earlier work this paper cites.
Unified deep supervised domain adaptation and generalization
Saeid Motiian, Marco Piccirilli, Donald A Adjeroh, and Gianfranco Doretto · 2017
Earlier work this paper cites.
Deep hashing network for unsupervised domain adaptation
Hemanth Venkateswara, Jose Eusebio, Shayok Chakraborty, and Sethuraman Panchanathan · 2017
Earlier work this paper cites.
Sampling matters in deep embedding learning
Chao-Yuan Wu, R Manmatha, Alexander J Smola, and Philipp Krahenbuhl · 2017
Earlier work this paper cites.
Benchmarking neural network robustness to common corruptions and perturbations
Dan Hendrycks and Thomas Dietterich · 2018
Earlier work this paper cites.
Learning deep representations by mutual information estimation and maximization
R Devon Hjelm, Alex Fedorov, Samuel Lavoie-Marchildon, Karan Grewal, Phil Bachman, Adam Trischler, and Yoshua Bengio · 2018
Earlier work this paper cites.
Learning to generalize: Meta-learning for domain generalization
Da Li, Yongxin Yang, Yi-Zhe Song, and Timothy Hospedales · 2018
Earlier work this paper cites.
Domain generalization with adversarial feature learning
Haoliang Li, Sinno Jialin Pan, Shiqi Wang, and Alex C Kot · 2018
Earlier work this paper cites.
Best sources forward: domain generalization through source-specific nets
Massimiliano Mancini, Samuel Rota Bulò, Barbara Caputo, and Elisa Ricci · 2018
Earlier work this paper cites.
Robust place categorization with deep domain generalization
Massimiliano Mancini, Samuel Rota Bulo, Barbara Caputo, and Elisa Ricci · 2018
Earlier work this paper cites.
Representation learning with contrastive predictive coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
Earlier work this paper cites.
Generalizing across domains via cross-gradient training
Shiv Shankar, Vihari Piratla, Soumen Chakrabarti, Siddhartha Chaudhuri, Preethi Jyothi, and Sunita Sarawagi · 2018
Cited alongside, same era.
Unsupervised feature learning via non-parametric instance discrimination
Zhirong Wu, Yuanjun Xiong, Stella X Yu, and Dahua Lin · 2018
Cited alongside, same era.
Generalizing to unseen domains via distribution matching
Isabela Albuquerque, João Monteiro, Mohammad Darvishi, Tiago H Falk, and Ioannis Mitliagkas · 2019
Cited alongside, same era.
Martin Arjovsky, Léon Bottou, Ishaan Gulrajani, and David Lopez-Paz · 2019
Cited alongside, same era.
Learning representations by maximizing mutual information across views
Philip Bachman, R Devon Hjelm, and William Buchwalter · 2019
Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2020
Later among the works it cites.
Data-efficient image recognition with contrastive predictive coding
Olivier Henaff · 2020
Later among the works it cites.
Qianjiang Hu, Xiao Wang, Wei Hu, and Guo-Jun Qi · 2020
Later among the works it cites.
Domain generalization via multidomain discriminant analysis
Shoubo Hu, Kun Zhang, Zhitang Chen, and Laiwan Chan · 2020
Later among the works it cites.
Self-challenging improves cross-domain generalization
Zeyi Huang, Haohan Wang, Eric P Xing, and Dong Huang · 2020
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
A meta-transfer objective for learning to disentangle causal mechanisms
Yoshua Bengio, Tristan Deleu, Nasim Rahaman, Nan Rosemary Ke, Sebastien Lachapelle, Olexa Bilaniuk, Anirudh Goyal, and Christopher Pal · 2019
Cited alongside, same era.
Domain generalization by solving jigsaw puzzles
Fabio M Carlucci, Antonio D’Innocente, Silvia Bucci, Barbara Caputo, and Tatiana Tommasi · 2019
Cited alongside, same era.
Domain generalization via model-agnostic learning of semantic features
Qi Dou, Daniel Coelho de Castro, Konstantinos Kamnitsas, and Ben Glocker · 2019
Cited alongside, same era.
Domain generalization via model-agnostic learning of semantic features
Qi Dou, Daniel Coelho de Castro, Konstantinos Kamnitsas, and Ben Glocker · 2019
Cited alongside, same era.
Exploring the landscape of spatial robustness
Logan Engstrom, Brandon Tran, Dimitris Tsipras, Ludwig Schmidt, and Aleksander Madry · 2019
Cited alongside, same era.
Episodic training for domain generalization
Da Li, Jianshu Zhang, Yongxin Yang, Cong Liu, Yi-Zhe Song, and Timothy M Hospedales · 2019
Cited alongside, same era.
Moment matching for multi-source domain adaptation
Xingchao Peng, Qinxun Bai, Xide Xia, Zijun Huang, Kate Saenko, and Bo Wang · 2019
Cited alongside, same era.
Domain generalization using a mixture of multiple latent domains
Toshihiko Matsuura and Tatsuya Harada · 2020
Later among the works it cites.
Efficient domain generalization via common-specific low-rank decomposition
Vihari Piratla, Praneeth Netrapalli, and Sunita Sarawagi · 2020
Later among the works it cites.
Learning to learn single domain generalization
Fengchun Qiao, Long Zhao, and Xi Peng · 2020
Later among the works it cites.
The pitfalls of simplicity bias in neural networks
Harshay Shah, Kaustav Tamuly, Aditi Raghunathan, Prateek Jain, and Praneeth Netrapalli · 2020
Later among the works it cites.
Fixmatch: Simplifying semi-supervised learning with consistency and confidence
Kihyuk Sohn, David Berthelot, Chun-Liang Li, Zizhao Zhang, Nicholas Carlini, Ekin D Cubuk, Alex Kurakin, Han Zhang, and Colin Raffel · 2020
Later among the works it cites.
What makes for good views for contrastive learning
Yonglong Tian, Chen Sun, Ben Poole, Dilip Krishnan, Cordelia Schmid, and Phillip Isola · 2020
Later among the works it cites.
Learning from extrinsic and intrinsic supervisions for domain generalization
Shujun Wang, Lequan Yu, Caizi Li, Chi-Wing Fu, and Pheng-Ann Heng · 2020
Later among the works it cites.
Unseen target stance detection with adversarial domain generalization
Zhen Wang, Qiansheng Wang, Chengguo Lv, Xue Cao, and Guohong Fu · 2020
Later among the works it cites.
Deep domain-adversarial image generation for domain generalisation
Kaiyang Zhou, Yongxin Yang, Timothy Hospedales, and Tao Xiang · 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.
When does contrastive learning preserve adversarial robustness from pretraining to finetuning?
Lijie Fan, Sijia Liu, Pin-Yu Chen, Gaoyuan Zhang, and Chuang Gan · 2021
Closest in time.
Towards non-iid image classification: A dataset and baselines
Yue He, Zheyan Shen, and Peng Cui · 2021
Closest in time.
Dual-stream multiple instance learning network for whole slide image classification with self-supervised contrastive learning
Bin Li, Yin Li, and Kevin W Eliceiri · 2021
Closest in time.
Towards out-of-distribution generalization: A survey
Zheyan Shen, Jiashuo Liu, Yue He, Xingxuan Zhang, Renzhe Xu, Han Yu, and Peng Cui · 2021
Closest in time.
Mi{ce}: Mixture of contrastive experts for unsupervised image clustering
Tsung Wei Tsai, Chongxuan Li, and Jun Zhu · 2021
Closest in time.
Contrastive learning for compact single image dehazing
Haiyan Wu, Yanyun Qu, Shaohui Lin, Jian Zhou, Ruizhi Qiao, Zhizhong Zhang, Yuan Xie, and Lizhuang Ma · 2021
Closest in time.
Why stable learning works? a theory of covariate shift generalization
Renzhe Xu, Peng Cui, Zheyan Shen, Xingxuan Zhang, and Tong Zhang · 2021
Closest in time.
Deep stable learning for out-of-distribution generalization
Xingxuan Zhang, Peng Cui, Renzhe Xu, Linjun Zhou, Yue He, and Zheyan Shen · 2021
Closest in time.
Towards domain generalization in object detection
Xingxuan Zhang, Zekai Xu, Renzhe Xu, Jiashuo Liu, Peng Cui, Weitao Wan, Chong Sun, and Chen Li · 2022
Closest in time.