351 citations · 733 across the 6 of their papers we have counts for
4 papers · 1 filter
Invariant Gaussian Process Latent Variable Models and Application in Causal Discovery
Kun Zhang, Bernhard Schoelkopf, Dominik Janzing
In nonlinear latent variable models or dynamic models, if we consider the latent variables as confounders (common causes), the noise dependencies imply further relations between th…
Source Separation and Higher-Order Causal Analysis of MEG and EEG
Kun Zhang, Aapo Hyvarinen
Separation of the sources and analysis of their connectivity have been an important topic in EEG/MEG analysis. To solve this problem in an automatic manner, we propose a two-layer…
Inferring deterministic causal relations
Povilas Daniusis, Dominik Janzing, Joris Mooij +4
We consider two variables that are related to each other by an invertible function. While it has previously been shown that the dependence structure of the noise can provide hints…
Kernel-based Conditional Independence Test and Application in Causal Discovery
Kun Zhang, Jonas Peters, Dominik Janzing +1
Conditional independence testing is an important problem, especially in Bayesian network learning and causal discovery. Due to the curse of dimensionality, testing for conditional…