I am also afflilated with the MPI for Biological Cybernetics as a research scientist.
KPC , Software to implement Nonlinear directed acyclic structure learning with weakly additive noise models (by Robert Tillman)
Consistent Nonparametric Tests of Independence , JMLR 2010
Hilbert Space Embeddings and Metrics on Probability Measures , JMLR 2010
Discussion of: Brownian distance covariance , Ann. App. Stat. 2009
Nonparametric Tree Graphical Models , AISTATS 2010
Arthur Gretton is a project scientist with the Machine Learning Department at Carnegie Mellon University since February 2009, and is affiliated as a research scientist with the Max Planck Institute for Biological Cybernetics, where he has worked since September 2002. He received degrees in physics and systems engineering from the Australian National University in 1996 and 1998, respectively; and studied machine learning from 1999 to 2003 with the Signal Processing and Communications Laboratory and Microsoft Research at the University of Cambridge, where he completed his PhD. His research interests include machine learning, kernel methods, statistical learning theory, nonparametric hypothesis testing, blind source separation, Gaussian processes, and non-parametric techniques for neural data analysis. He has been an associate editor at IEEE Transactions on Pattern Analysis and Machine Intelligence since March 2009, and a member of the NIPS Program Committee in 2008 and 2009.