title: Relational Learning with Variational Bayes
abstract: In psychology, relational learning refers to the ability to recognize and respond to
  relationship among objects irrespective of the nature of those objects. Relational
  learning has long been recognized as a hallmark of human cognition and a key
  question in artificial intelligence research. In this work, we propose an unsupervised
  learning method for addressing the relational learning problem where we
  learn the underlying relationship between a pair of data irrespective of the nature
  of those data. The central idea of the proposed method is to encapsulate the relational
  learning problem with a probabilistic graphical model in which we perform
  inference to learn about data relationships and other relational processing tasks.
authors: Kuang-Hung Liu
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