## Bayesian and Bayesian Nonparametric Dynamic Modeling

Relevant Resources: Graphs of Time Series, Discovering Clusters of Correlated Time Series, Joint Modeling of Multiple Time Series via the Beta Process, Multiresolution Gaussian Processes, Sticky HDP-HMM, HDP Switching Linear Dynamical System, Magazine article on BNP Markov Switching Processes, Book chapter on Mixed Membership Modeling for Time Series, PhD Thesis

## Large-Scale and Streaming Bayesian Inference

Relevant Papers: Streaming BNP Clustering, Stochastic Variational Inference for HMMs, Stochastic Gradient HMC, Split-Merge MCMC for Beta Process HMM

## Inference and Learning of Determinantal Point Processes

Relevant Papers: EM for Learning DPPs, Learning DPP Kernel Parameters, Approximate Inference in Continuous DPPs, Nystrom Approximation for Large-Scale DPPs, Markov DPPs

## Covariance Processes

Relevant Papers: Inverse Wishart AR Processes, BNP Covariance Regression

## Modeling of Neuroimaging Data

Relevant Papers: Capturing Complex Dynamics and Evolving Correlations in EEG, Parsing Epileptic Events, Bayesian Hierarchical Models of Brain Activation in MEG

## Bayesian Network Modeling

Relevant Papers: Sparse Graphs using Exchangeable Random Measures, Predicting the Popularity of Tweets