References
- Carpenter, B., Gelman, A., Hoffman, M. D., Lee, D., Goodrich, B., Betancourt, M., Brubaker, M., Guo, J., Li, P., and Riddell, A. (2016), “Stan: A Probabilistic Programming Language,” Journal of Statistical Software, 76, 1–32.
- Diaconis, P., and Ylvisaker, D. (1979), “Conjugate Priors for Exponential Families,” The Annals of Statistics, 7, 269–281.
- Gelman, A., Vehtari, A., Jylänki, P., Robert, C., Chopin, N., and Cunningham, J. P. (2014), “Expectation Propagation as a Way of Life,” arXiv preprint arXiv:1412.4869.
- Hoffman, M. D., Blei, D. M., Wang, C., and Paisley, J. (2013), “Stochastic Variational Inference,” Journal of Machine Learning Research, 14, 1303–1347.
- Hoffman, M. D., and Gelman, A. (2014), “The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo,” Journal of Machine Learning Research, 15, 1593–1623.
- Huang, Z., and Gelman, A. (2005), “Sampling for Bayesian Computation With Large Datasets,” Technical Report.
- Jordan, M. I. (2013), “On Statistics, Computation and Scalability,” Bernoulli, 19, 1378–1390.
- Kucukelbir, A., Tran, D., Ranganath, R., Gelman, A., and Blei, D. M. (2016), “Automatic Differentiation Variational Inference,” Journal of Machine Learning Research, to appear.
- Tran, D., Gelman, A., and Vehtari, A. (2016), “Gradient-Based Marginal Optimization,” Technical Report.
- Wand, M. P. (2017), “Fast Approximate Inference for Arbitrarily Large Semiparametric Regression Models via Message Passing,” Journal of the American Statistical Association, this issue.
- Wang, X., and Dunson, D. B. (2013), “Parallelizing MCMC via Weierstrass Sampler,” arXiv preprint arXiv:1312.4605.