118 citations · 235 across the 20 of their papers we have counts for
4 papers · 1 filter
On Learning Domain-Invariant Representations for Transfer Learning with Multiple Sources
Trung Phung, Trung Le, Long Vuong +4
Domain adaptation (DA) benefits from the rigorous theoretical works that study its insightful characteristics and various aspects, e.g., learning domain-invariant representations a…
Exploiting Domain-Specific Features to Enhance Domain Generalization
Manh-Ha Bui, Toan Tran, Anh Tuan Tran +1
Domain Generalization (DG) aims to train a model, from multiple observed source domains, in order to perform well on unseen target domains. To obtain the generalization capability,…
KL Guided Domain Adaptation
A. Tuan Nguyen, Toan Tran, Yarin Gal +2
Domain adaptation is an important problem and often needed for real-world applications. In this problem, instead of i.i.d. training and testing datapoints, we assume that the sourc…
Domain Invariant Representation Learning with Domain Density Transformations
A. Tuan Nguyen, Toan Tran, Yarin Gal +1
Domain generalization refers to the problem where we aim to train a model on data from a set of source domains so that the model can generalize to unseen target domains. Naively tr…