No voodoo here! Learning discrete graphical models via inverse covariance estimation
Latent Force Models with Gaussian Processes
Dimensionality Reduction
Models, assumptions and confidence limits
Network Inference via the Time­Varying Graphical Lasso
Statistical Methods
Borrowing Strength, Learning Vector Valued Functions and Supervised Dimension Reduction
Towards a Learning Theory of Cause-Effect Inference
Statistical Classification and Cluster Processes
Spectral learning of linear dynamics from generalisedlinear observations with application to neural population data