Lecture 2: Mappings of Probabilities to RKHS and Applications MLSS Cadiz, 2016 Arthur Gretton Gatsby Unit, CSML, UCL

Source URL: learning.mpi-sws.org

Lecture 3: Dependence measures using RKHS embeddings MLSS T¨ ubingen, 2015 Arthur Gretton Gatsby Unit, CSML, UCL

Source URL: mlss.tuebingen.mpg.de

Journal of Machine Learning Research1423 Submitted 4/08; Revised 8/09; Published 4/10 Consistent Nonparametric Tests of Independence Arthur Gretton∗

Source URL: www.gatsby.ucl.ac.uk

Optimal kernel choice for kernel hypothesis testing Arthur Gretton Gatsby Computational Neuroscience Unit MSR, Nov. 2012

Source URL: www.gatsby.ucl.ac.uk

Distinguishing Distributions with Interpretable Features Wittawat Jitkrittum Zoltán Szabó Kacper Chwialkowski Arthur Gretton

Source URL: www.gatsby.ucl.ac.uk

Lecture 3: Dependence measures using RKHS embeddings MLSS T¨ ubingen, 2015 Arthur Gretton Gatsby Unit, CSML, UCL

Source URL: www.gatsby.ucl.ac.uk

Learning with probabilities as inputs, using kernels Arthur Gretton Gatsby Computational Neuroscience Unit NIPS workshop on Probabilistic Numerics, 2015

Source URL: www.gatsby.ucl.ac.uk

Nonlinear directed acyclic structure learning with weakly additive noise models Peter Spirtes Arthur Gretton Robert E. Tillman

Source URL: select.cs.cmu.edu

• Statistics
• Analysis
• Data
• Statistical models
• Multivariate statistics
• Signal processing
• Data analysis
• Independent component analysis
• Time series analysis
• Additive white Gaussian noise
• Gaussian function
• Positive-definite kernel

Nonparametric Tree Graphical Models via Kernel Embeddings 1 Le Song,1 Arthur Gretton,1,2 Carlos Guestrin1 School of Computer Science, Carnegie Mellon University; 2 MPI for Biological Cybernetics

Source URL: www.gatsby.ucl.ac.uk

Optimal kernel choice for large-scale two-sample tests Arthur Gretton,1,3 Bharath Sriperumbudur,1 Dino Sejdinovic,1 Heiko Strathmann2 1 Gatsby Unit and 2 CSD, CSML, UCL, UK; 3 MPI for Intelligent Systems, Germany {arthu

Source URL: www.gatsby.ucl.ac.uk