Given multiple possible models b1, b2, . . . bn for a protein structure, a common sub-task in in-silico Protein Structure Prediction is ranking these models according to their qua...
The infinite hidden Markov model is a nonparametric extension of the widely used hidden Markov model. Our paper introduces a new inference algorithm for the infinite Hidden Markov...
Jurgen Van Gael, Yunus Saatci, Yee Whye Teh, Zoubi...
Discovering additive structure is an important step towards understanding a complex multi-dimensional function because it allows the function to be expressed as the sum of lower-d...
Stationarity is often an unrealistic prior assumption for Gaussian process regression. One solution is to predefine an explicit nonstationary covariance function, but such covaria...
A family of probabilistic time series models is developed to analyze the time evolution of topics in large document collections. The approach is to use state space models on the n...