602 citations · 2.9k across the 103 of their papers we have counts for
7 papers · 1 filter
Filtering with State-Observation Examples via Kernel Monte Carlo Filter
Motonobu Kanagawa, Yu Nishiyama, Arthur Gretton +1
This paper addresses the problem of filtering with a state-space model. Standard approaches for filtering assume that a probabilistic model for observations (i.e. the observation m…
Density Estimation in Infinite Dimensional Exponential Families
Bharath Sriperumbudur, Kenji Fukumizu, Arthur Gretton +2
In this paper, we consider an infinite dimensional exponential family, of probability densities, which are parametrized by functions in a reproducing kernel Hilbert s…
Hilbert Space Embeddings of Predictive State Representations
Byron Boots, Geoffrey Gordon, Arthur Gretton
Predictive State Representations (PSRs) are an expressive class of models for controlled stochastic processes. PSRs represent state as a set of predictions of future observable eve…
Kernel Adaptive Metropolis-Hastings
Dino Sejdinovic, Heiko Strathmann, Maria Lomeli Garcia +2
A Kernel Adaptive Metropolis-Hastings algorithm is introduced, for the purpose of sampling from a target distribution with strongly nonlinear support. The algorithm embeds the traj…
B-tests: Low Variance Kernel Two-Sample Tests
Wojciech Zaremba, Arthur Gretton, Matthew Blaschko
A family of maximum mean discrepancy (MMD) kernel two-sample tests is introduced. Members of the test family are called Block-tests or B-tests, since the test statistic is an avera…
A Kernel Test for Three-Variable Interactions
Dino Sejdinovic, Arthur Gretton, Wicher Bergsma
We introduce kernel nonparametric tests for Lancaster three-variable interaction and for total independence, using embeddings of signed measures into a reproducing kernel Hilbert s…