Generalizing to unseen domains: A survey on domain generalization
Machine learning systems generally assume that the training and testing distributions are
the same. To this end, a key requirement is to develop models that can generalize to unseen …
the same. To this end, a key requirement is to develop models that can generalize to unseen …
Generalizing to Unseen Domains: A Survey on Domain Generalization
J Wang, C Lan, C Liu, Y Ouyang, T Qin, W Lu… - IEEE Transactions on …, 2023 - dl.acm.org
Machine learning systems generally assume that the training and testing distributions are
the same. To this end, a key requirement is to develop models that can generalize to unseen …
the same. To this end, a key requirement is to develop models that can generalize to unseen …
[PDF][PDF] Generalizing to Unseen Domains: A Survey on Domain Generalization
J Wang, C Lan, C Liu, Y Ouyang, T Qin - academia.edu
Abstract Domain generalization (DG), ie, out-ofdistribution generalization, has attracted
increasing interests in recent years. Domain generalization deals with a challenging setting …
increasing interests in recent years. Domain generalization deals with a challenging setting …
[PDF][PDF] Generalizing to Unseen Domains: A Survey on Domain Generalization
J Wang - wentingzhang.org
• Kingma DP, Welling M. Auto-encoding variational bayes [J]. arXiv preprint arXiv:
1312.6114, 2013.• Goodfellow I, Pouget-Abadie J, Mirza M, et al. Generative adversarial …
1312.6114, 2013.• Goodfellow I, Pouget-Abadie J, Mirza M, et al. Generative adversarial …
Generalizing to Unseen Domains: A Survey on Domain Generalization
J Wang, C Lan, C Liu, Y Ouyang, T Qin, W Lu… - IEEE Transactions on …, 2023 - computer.org
Abstract Machine learning systems generally assume that the training and testing
distributions are the same. To this end, a key requirement is to develop models that can …
distributions are the same. To this end, a key requirement is to develop models that can …
Generalizing to Unseen Domains: A Survey on Domain Generalization
J Wang, C Lan, C Liu, Y Ouyang, T Qin, W Lu… - arXiv e …, 2021 - ui.adsabs.harvard.edu
Abstract Machine learning systems generally assume that the training and testing
distributions are the same. To this end, a key requirement is to develop models that can …
distributions are the same. To this end, a key requirement is to develop models that can …
Generalizing to Unseen Domains: A Survey on Domain Generalization
J Wang, C Lan, C Liu, Y Ouyang, T Qin - Proceedings of the Thirtieth …, 2021 - cir.nii.ac.jp
抄録< jats: p> Domain generalization (DG), ie, out-of-distribution generalization, has
attracted increased interests in recent years. Domain generalization deals with a …
attracted increased interests in recent years. Domain generalization deals with a …
[PDF][PDF] Generalizing to Unseen Domains: A Survey on Domain Generalization
J Wang, C Lan, C Liu, Y Ouyang, T Qin - ijcai.org
Abstract Domain generalization (DG), ie, out-ofdistribution generalization, has attracted
increasing interests in recent years. Domain generalization deals with a challenging setting …
increasing interests in recent years. Domain generalization deals with a challenging setting …
[PDF][PDF] Generalizing to Unseen Domains: A Survey on Domain Generalization
J Wang, C Lan, C Liu, Y Ouyang, T Qin - scholar.archive.org
Abstract Domain generalization (DG), ie, out-ofdistribution generalization, has attracted
increasing interests in recent years. Domain generalization deals with a challenging setting …
increasing interests in recent years. Domain generalization deals with a challenging setting …
[PDF][PDF] Generalizing to Unseen Domains: A Survey on Domain Generalization
J Wang, C Lan, C Liu, Y Ouyang, T Qin - researchgate.net
Abstract Domain generalization (DG), ie, out-ofdistribution generalization, has attracted
increasing interests in recent years. Domain generalization deals with a challenging setting …
increasing interests in recent years. Domain generalization deals with a challenging setting …