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Domain Generalization (DG) aims to learn a model that can generalize well to unseen target domains from a set of source domains.
Arjovsky, M.; Bottou, L.; Gulrajani, I.; and Lopez-Paz, D. 2019 · 1907
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Sagawa, S.; Koh, P. W.; Hashimoto, T. B.; and Liang, P. 2019 · 1911
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The nature of statistical learning theory
Vapnik, V. 1999 · 1999
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Improve unsupervised domain adaptation with mixup training
Yan, S.; Song, H.; Li, N.; Zou, L.; and Ren, L. 2020 · 2001
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In search of lost domain generalization
Gulrajani, I.; and Lopez-Paz, D. 2020 · 2007
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Adaptive Risk Minimization: Learning to Adapt to Domain Shift
Zhang, M.; Marklund, H.; Dhawan, N.; Gupta, A.; Levine, S.; and Finn, C. 2020 · 2007
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Visualizing data using t-SNE
Van der Maaten, L.; and Hinton, G. 2008 · 2008
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Deep residual learning for image recognition
He, K.; Zhang, X.; Ren, S.; and Sun, J. 2016 · 2016
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Deep coral: Correlation alignment for deep domain adaptation
Sun, B.; and Saenko, K. 2016 · 2016
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Domain generalization by marginal transfer learning
Blanchard, G.; Deshmukh, A. A.; Dogan, U.; Lee, G.; and Scott, C. 2017 · 2017
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Deeper, broader and artier domain generalization
Li, D.; Yang, Y.; Song, Y.-Z.; and Hospedales, T. M. 2017 · 2017
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Deep hashing network for unsupervised domain adaptation
Venkateswara, H.; Eusebio, J.; Chakraborty, S.; and Panchanathan, S. 2017 · 2017
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Metareg: Towards domain generalization using meta-regularization
Balaji, Y.; Sankaranarayanan, S.; and Chellappa, R. 2018 · 2018
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Recognition in terra incognita
Beery, S.; Van Horn, G.; and Perona, P. 2018 · 2018
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Domain Generalization via Conditional Invariant Representations
Li, Y.; Gong, M.; Tian, X.; Liu, T.; and Tao, D. 2018c · 2018
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Generalizing Across Domains via Cross-Gradient Training
Shankar, S.; Piratla, V.; Chakrabarti, S.; Chaudhuri, S.; Jyothi, P.; and Sarawagi, S. 2018 · 2018
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Generalizing to unseen domains via adversarial data augmentation
Volpi, R.; Namkoong, H.; Sener, O.; Duchi, J. C.; Murino, V.; and Savarese, S. 2018 · 2018
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Domain Generalization by Solving Jigsaw Puzzles
Carlucci, F. M.; D’Innocente, A.; Bucci, S.; Caputo, B.; and Tommasi, T. 2019 · 2019
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Domain generalization via model-agnostic learning of semantic features
Dou, Q.; de Castro, D. C.; Kamnitsas, K.; and Glocker, B. 2019 · 2019
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A Simple Framework for Contrastive Learning of Visual Representations
Chen, T.; Kornblith, S.; Norouzi, M.; and Hinton, G. E. 2020 · 2020
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Momentum contrast for unsupervised visual representation learning
Transferable query selection for active domain adaptation
Fu, B.; Cao, Z.; Wang, J.; and Long, M. 2021 · 2021
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Out-of-distribution generalization via risk extrapolation (rex)
Krueger, D.; Caballero, E.; Jacobsen, J.-H.; Zhang, A.; Binas, J.; Zhang, D.; Le Priol, R.; and Courville, A. 2021 · 2021
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Learning causal semantic representation for out-of-distribution prediction
Liu, C.; Sun, X.; Wang, J.; Tang, H.; Li, T.; Qin, T.; Chen, W.; and Liu, T.-Y. 2021 · 2021
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Domain generalization using causal matching
Mahajan, D.; Tople, S.; and Sharma, A. 2021 · 2021
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Reducing domain gap by reducing style bias
Nam, H.; Lee, H.; Park, J.; Yoon, W.; and Yoo, D. 2021 · 2021
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Fishr: Invariant gradient variances for out-of-distribution generalization
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He, K.; Fan, H.; Wu, Y.; Xie, S.; and Girshick, R. 2020 · 2020
Cited alongside, same era.
Self-challenging improves cross-domain generalization
Huang, Z.; Wang, H.; Xing, E. P.; and Huang, D. 2020 · 2020
Cited alongside, same era.
Domain Generalization Using a Mixture of Multiple Latent Domains
Matsuura, T.; and Harada, T. 2020 · 2020
Cited alongside, same era.
Test-time training with self-supervision for generalization under distribution shifts
Sun, Y.; Wang, X.; Liu, Z.; Miller, J.; Efros, A.; and Hardt, M. 2020 · 2020
Cited alongside, same era.
Learning from Extrinsic and Intrinsic Supervisions for Domain Generalization
Wang, S.; Yu, L.; Li, C.; Fu, C.-W.; and Heng, P. 2020 · 2020
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Domain Generalization via Entropy Regularization
Zhao, S.; Gong, M.; Liu, T.; Fu, H.; and Tao, D. 2020 · 2020
Cited alongside, same era.
Deep Domain-Adversarial Image Generation for Domain Generalisation
Zhou, K.; Yang, Y.; Hospedales, T. M.; and Xiang, T. 2020b · 2020
Cited alongside, same era.
Rame, A.; Dancette, C.; and Cord, M. 2021 · 2021
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Shahtalebi, S.; Gagnon-Audet, J.-C.; Laleh, T.; Faramarzi, M.; Ahuja, K.; and Rish, I. 2021 · 2021
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Recovering Latent Causal Factor for Generalization to Distributional Shifts
Sun, X.; Wu, B.; Zheng, X.; Liu, C.; Chen, W.; Qin, T.; and Liu, T.-Y. 2021 · 2021
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On calibration and out-of-domain generalization
Wald, Y.; Feder, A.; Greenfeld, D.; and Shalit, U. 2021 · 2021
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Understanding the behaviour of contrastive loss
Wang, F.; and Liu, H. 2021 · 2021
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Causal attention for vision-language tasks
Yang, X.; Zhang, H.; Qi, G.; and Cai, J. 2021 · 2021
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Learning Domain-Invariant Relationship with Instrumental Variable for Domain Generalization
Yuan, J.; Ma, X.; Kuang, K.; Xiong, R.; Gong, M.; and Lin, L. 2021 · 2021
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Deep stable learning for out-of-distribution generalization
Zhang, X.; Cui, P.; Xu, R.; Zhou, L.; He, Y.; and Shen, Z. 2021 · 2021
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Domain Generalization with Mixstyle
Zhou, K.; Yang, Y.; Qiao, Y.; and Xiang, T. 2021 · 2021
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Domain-adversarial training of neural networks
Ganin, Y.; Ustinova, E.; Ajakan, H.; Germain, P.; Larochelle, H.; Laviolette, F.; Marchand, M.; and Lempitsky, V. 2016 · 2030
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