Bayesian Research Kitchen Workshop (BARK), Grasmere 2008
13 Videos · Sep 6, 2008
About
Motivation\ 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.
Themes\ * 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.
Videos
Bayeswatch
Feb 18, 2024 8 views
The role of mechanistic models in Bayesian inference
Oct 9, 2008 3632 views
Negotiated Interaction : Iterative Inference and Feedback of Intention in HCI
Oct 9, 2008 3570 views
Variational Model Selection for Sparse Gaussian Process Regression
Oct 9, 2008 6228 views
Multi-task Learning with Gaussian Processes
Oct 9, 2008 6319 views
On the relation between Bayesian inference and certain solvable problems of stoc...
Oct 9, 2008 4682 views
Bayesian learning of sparse factor loadings
Oct 9, 2008 5309 views
Should all Machine Learning be Bayesian? Should all Bayesian models be non-param...
Oct 9, 2008 27911 views
Probabilistic models for ranking and information extraction
Oct 9, 2008 3220 views
Well-known shortcomings, advantages and computational challenges in Bayesian mod...
Oct 9, 2008 4557 views
Covariance functions and Bayes errors for GP regression on random graphs
Oct 9, 2008 3835 views
Introduction to BARK 2008
Oct 9, 2008 3136 views
Latent Force Models with Gaussian Processes
Oct 9, 2008 4992 views