Bayesian Research Kitchen Workshop (BARK), Grasmere 2008
The main aim of this workshop is to allow leading Bayesian researchers in machine learning to get together presenting their latest ideas and discussing future directions.
- Incorporating Complex Prior Knowledge in Bayesian inference, for example mechanistic models (such as differential equations) or knowledge transfered from other related situations (e.g. hierarchical Dirichlet Processes).
- Model mismatch: the Bayesian lynch pin is that the model is correct, but it rarely is.
- Approximation techniques: how should we do Bayesian inference in practice. Sampling, variational, Laplace or something else?
- Your pet Bayesian issue here.
Visit the Workshop website here.