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Found 5 papers, 3 papers with code
Gene Regulatory Network Inference in the Presence of Dropouts: a Causal View
This particular test-wise deletion procedure, in which we perform CI tests on the samples without zeros for the conditioned variables, can be seamlessly integrated with existing structure learning approaches including constraint-based and greedy score-based methods, thus giving rise to a principled framework for GRNI in the presence of dropouts.
Partial Identifiability for Domain Adaptation
In general, without further assumptions, the joint distribution of the features and the label is not identifiable in the target domain.
Domain Adaptation with Invariant Representation Learning: What Transformations to Learn?
We provide reasoning why when the supports of the source and target data from overlap, any map of $X$ that is fixed across domains may not be suitable for domain adaptation via invariant features.
Domain Adaptation as a Problem of Inference on Graphical Models
Such a graphical model distinguishes between constant and varied modules of the distribution and specifies the properties of the changes across domains, which serves as prior knowledge of the changing modules for the purpose of deriving the posterior of the target variable $Y$ in the target domain.
On Domain Transfer When Predicting Intent in Text
In many domains, especially enterprise text analysis, there is an abundance of data which can be used for the development of new AI-powered intelligent experiences to improve people's productivity.
