1. Allen, T. V., & Greiner, R. (2000). Model selection criteria for learning belief nets: an empirical comparison. In Proceedings of international conference on machine learning (pp. 1047–1054).
2. Attias, H. (1999). Inferring parameters and structure of latent variable models by variational Bayes. In Proceedings of uncertainty in artificial intelligence (pp. 21–30). Stockholm, Sweden.
3. Beal, M. J. (2003). Variational algorithms for approximate Bayesian inference. Ph.D. Thesis, University College London.
4. Beal, M. J., & Ghahramani, Z. (2003). The variational Bayesian EM algorithm for incomplete data: with application to scoring graphical model structures. In Bayesian statistics (Vol. 7). London: Oxford University Press.
5. Friedman, N. (2004). Inferring cellular networks using probabilistic graphical models. Science, 303, 799–805.