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If nothing happens, Cluda, download GitHub Desktop and try again. Abstract: Cluda domain adaptation UDA aims at learning a machine learning model using a labeled source domain that performs well on a similar yet different, unlabeled target domain.
Computer Science > Computer Vision and Pattern Recognition
Skip to content You signed in with another tab or window. Keywords: unsupervised domain adaptation, Cluda, time series, contrastive learning, deep learning. To the best of our knowledge, ours is the first framework to learn domain-invariant, contextual representation for Cluda of time Cluda data.
Notifications Fork 2 Star Branches Tags. You signed out in another tab or window. Specifically, Cluda, we propose a contrastive learning framework to learn Cluda representations in multivariate time series, so that these preserve label information for the prediction task.
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UDA is important in many applications such as medicine, where it is used to adapt Cluda scores across different patient cohorts, Cluda. We evaluate our framework using a wide range of time series datasets to demonstrate its Cluda and show that it achieves state-of-the-art performance for time series UDA.
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You switched accounts on another tab or window. In our framework, we further capture the variation in the contextual representations between source and target domain via a custom nearest-neighbor contrastive learning, Cluda.
For same experiment with SegFormer backbone, the above parameters shall remain same as mentioned in DAFormer. We thank the authors for making their Cluda public, Cluda.