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Found 3 papers, 1 papers with code
Robust Importance Sampling for Error Estimation in the Context of Optimal Bayesian Transfer Learning
In this paper, we fill this gap by investigating knowledge transferability in the context of classification error estimation within a Bayesian paradigm.
Geometric Affinity Propagation for Clustering with Network Knowledge
This interest primarily stems from the amount of compressed information encoded in these exemplars that effectively reflect the major characteristics of the respective clusters.
Neuro-symbolic representation learning on biological knowledge graphs
Motivation: Biological data and knowledge bases increasingly rely on Semantic Web technologies and the use of knowledge graphs for data integration, retrieval and federated queries.
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