NIPS Proceedings
^{β}
Books
Arthur Gretton
25 Papers
BRUNO: A Deep Recurrent Model for Exchangeable Data
(2018)
Informative Features for Model Comparison
(2018)
On gradient regularizers for MMD GANs
(2018)
A Linear-Time Kernel Goodness-of-Fit Test
(2017)
Interpretable Distribution Features with Maximum Testing Power
(2016)
Fast Two-Sample Testing with Analytic Representations of Probability Measures
(2015)
Gradient-free Hamiltonian Monte Carlo with Efficient Kernel Exponential Families
(2015)
A Wild Bootstrap for Degenerate Kernel Tests
(2014)
A Kernel Test for Three-Variable Interactions
(2013)
B-test: A Non-parametric, Low Variance Kernel Two-sample Test
(2013)
Optimal kernel choice for large-scale two-sample tests
(2012)
Kernel Bayes' Rule
(2011)
A Fast, Consistent Kernel Two-Sample Test
(2009)
Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions
(2009)
Nonlinear directed acyclic structure learning with weakly additive noise models
(2009)
Characteristic Kernels on Groups and Semigroups
(2008)
Kernel Measures of Independence for non-iid Data
(2008)
Learning Taxonomies by Dependence Maximization
(2008)
A Kernel Statistical Test of Independence
(2007)
Colored Maximum Variance Unfolding
(2007)
Kernel Measures of Conditional Dependence
(2007)
A Kernel Method for the Two-Sample-Problem
(2006)
Correcting Sample Selection Bias by Unlabeled Data
(2006)
Statistical Convergence of Kernel CCA
(2005)
Ranking on Data Manifolds
(2003)