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In the domain generalization literature, a common objective is to learn representations independent of the domain after conditioning on the class label.
Feature-critic networks for heterogeneous domain generalization
Li, Y., Yang, Y., Zhou, W., and Hospedales, T. M · 1901
Earlier work this paper cites.
On loss functions which minimize to conditional expected values and posterior probabilities
Miller, J. W., Goodman, R., and Smyth, P · 1993
Earlier work this paper cites.
Improving out-of-distribution generalization via multi-task self-supervised pretraining
Albuquerque, I., Naik, N., Li, J., Keskar, N., and Socher, R · 2003
Earlier work this paper cites.
Visualizing data using t-sne
Maaten, L. v. d. and Hinton, G · 2008
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Causality
Pearl, J · 2009
Earlier work this paper cites.
Domain generalization via invariant feature representation
Muandet, K., Balduzzi, D., and Schölkopf, B · 2013
Earlier work this paper cites.
Explaining and harnessing adversarial examples
Goodfellow, I. J., Shlens, J., and Szegedy, C · 2014
Earlier work this paper cites.
Domain generalization for object recognition with multi-task autoencoders
Ghifary, M., Bastiaan Kleijn, W., Zhang, M., and Balduzzi, D · 2015
Earlier work this paper cites.
Domain-adversarial training of neural networks
Ganin, Y., Ustinova, E., Ajakan, H., Germain, P., Larochelle, H., Laviolette, F., Marchand, M., and Lempitsky, V · 2016
Earlier work this paper cites.
Scatter component analysis: A unified framework for domain adaptation and domain generalization
Ghifary, M., Balduzzi, D., Kleijn, W. B., and Zhang, M · 2016
Earlier work this paper cites.
Domain adaptation with conditional transferable components
Gong, M., Zhang, K., Liu, T., Tao, D., Glymour, C., and Schölkopf, B · 2016
Earlier work this paper cites.
Causal inference by using invariant prediction: identification and confidence intervals
Peters, J., Bühlmann, P., and Meinshausen, N · 2016
Earlier work this paper cites.
Deep coral: Correlation alignment for deep domain adaptation
Sun, B. and Saenko, K · 2016
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Deeper, broader and artier domain generalization
Li, D., Yang, Y., Song, Y.-Z., and Hospedales, T. M · 2017
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Unified deep supervised domain adaptation and generalization
Motiian, S., Piccirilli, M., Adjeroh, D. A., and Doretto, G · 2017
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Chestx-ray8: Hospital-scale chest x-ray database and benchmarks on weakly-supervised classification and localization of common thorax diseases
Wang, X., Peng, Y., Lu, L., Lu, Z., Bagheri, M., and Summers, R. M · 2017
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URL https://www.kaggle.com/c/rsna-pneumonia-detection-challenge
Kaggle: Rsna pneumonia detection challenge, 2018 · 2018
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Metareg: Towards domain generalization using meta-regularization
Balaji, Y., Sankaranarayanan, S., and Chellappa, R · 2018
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Domain generalization with domain-specific aggregation modules
D’Innocente, A. and Caputo, B · 2018
Earlier work this paper cites.
Domain adaptation by using causal inference to predict invariant conditional distributions
Magliacane, S., van Ommen, T., Claassen, T., Bongers, S., Versteeg, P., and Mooij, J. M · 2018
Cited alongside, same era.
Invariant models for causal transfer learning
Rojas-Carulla, M., Schölkopf, B., Turner, R., and Peters, J · 2018
Cited alongside, same era.
Generalizing across domains via cross-gradient training
Shankar, S., Piratla, V., Chakrabarti, S., Chaudhuri, S., Jyothi, P., and Sarawagi, S · 2018
Cited alongside, same era.
Generalizing to unseen domains via adversarial data augmentation
Volpi, R., Namkoong, H., Sener, O., Duchi, J. C., Murino, V., and Savarese, S · 2018
Cited alongside, same era.
Adversarial invariant feature learning with accuracy constraint for domain generalization
Akuzawa, K., Iwasawa, Y., and Matsuo, Y · 2019
Cited alongside, same era.
On learning invariant representation for domain adaptation
Zhao, H., Combes, R. T. d., Zhang, K., and Gordon, G. J · 2019
Later among the works it cites.
Invariant risk minimization games
Ahuja, K., Shanmugam, K., Varshney, K., and Dhurandhar, A · 2020
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A simple framework for contrastive learning of visual representations
Chen, T., Kornblith, S., Norouzi, M., and Hinton, G · 2020
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A causal framework for distribution generalization
Christiansen, R., Pfister, N., Jakobsen, M. E., Gnecco, N., and Peters, J · 2020
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On the limits of cross-domain generalization in automated x-ray prediction
Cohen, J. P., Hashir, M., Brooks, R., and Bertrand, H · 2020
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Arjovsky, M., Bottou, L., Gulrajani, I., and Lopez-Paz, D · 2019
Cited alongside, same era.
Towards shape biased unsupervised representation learning for domain generalization
Asadi, N., Sarfi, A. M., Hosseinzadeh, M., Karimpour, Z., and Eftekhari, M · 2019
Cited alongside, same era.
Domain generalization by solving jigsaw puzzles
Carlucci, F. M., D’Innocente, A., Bucci, S., Caputo, B., and Tommasi, T · 2019
Cited alongside, same era.
Domain generalization via model-agnostic learning of semantic features
Dou, Q., de Castro, D. C., Kamnitsas, K., and Glocker, B · 2019
Cited alongside, same era.
Momentum contrast for unsupervised visual representation learning
He, K., Fan, H., Wu, Y., Xie, S., and Girshick, R · 2019
Cited alongside, same era.
Conditional variance penalties and domain shift robustness
Heinze-Deml, C. and Meinshausen, N · 2019
Cited alongside, same era.
Domain generalization via multidomain discriminant analysis
Hu, S., Zhang, K., Chen, Z., and Chan, L · 2019
Cited alongside, same era.
Closest in time.
In search of lost domain generalization
Gulrajani, I. and Lopez-Paz, D · 2020
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Self-challenging improves cross-domain generalization
Huang, Z., Wang, H., Xing, E. P., and Huang, D · 2020
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Diva: Domain invariant variational autoencoders
Ilse, M., Tomczak, J. M., Louizos, C., and Welling, M · 2020
Closest in time.
Out-of-distribution generalization via risk extrapolation (rex)
Krueger, D., Caballero, E., Jacobsen, J.-H., Zhang, A., Binas, J., Priol, R. L., and Courville, A · 2020
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Sequential learning for domain generalization
Li, D., Yang, Y., Song, Y.-Z., and Hospedales, T · 2020
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Domain generalization using a mixture of multiple latent domains
Matsuura, T. and Harada, T · 2020
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Efficient domain generalization via common-specific low-rank decomposition
Piratla, V., Netrapalli, P., and Sarawagi, S · 2020
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Correlation-aware adversarial domain adaptation and generalization
Rahman, M. M., Fookes, C., Baktashmotlagh, M., and Sridharan, S · 2020
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The pitfalls of simplicity bias in neural networks
Shah, H., Tamuly, K., Raghunathan, A., Jain, P., and Netrapalli, P · 2020
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Heterogeneous domain generalization via domain mixup
Wang, Y., Li, H., and Kot, A. C · 2020
Closest in time.
Improve unsupervised domain adaptation with mixup training
Yan, S., Song, H., Li, N., Zou, L., and Ren, L · 2020
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Domain generalization via entropy regularization
Zhao, S., Gong, M., Liu, T., Fu, H., and Tao, D · 2020
Closest in time.
Deep domain-adversarial image generation for domain generalisation
Zhou, K., Yang, Y., Hospedales, T. M., and Xiang, T · 2020
Closest in time.