## Tutorials

 Dec 2019 NeurIPS 2019 Tutorial: Interpretable Comparison of Distributions and Models Video. Slides (part 1, part 2, part 3). Mar 2018 Machine Learning Fundamentals VISTEC, Rayong, Thailand. The first part of a series of four talks. Event details here. Mar 2018 Introduction to Kernel Methods for Comparing Distributions BKK Machine Learning Meetup, Bangkok.

## Research

 Oct 2019 Informative Features for Model Comparison Swiss Data Science Center (invited talk) Sep 2019 Informative Features for Comparing Distributions Feb 2018 A Linear-Time Kernel Goodness-of-Fit Test Jun 2017 The Finite-Set Independence Criterion (FSIC) Feb 2017 An Adaptive Test of Independence with Analytic Kernel Embeddings Dec 2016 Interpretable Distribution Features with Maximum Testing Power NeurIPS 2016 May 2016 K2-ABC: Approximate Bayesian Computation with Kernel Embeddings AISTATS 2016 Dec 2015 Locally Linear Latent Variable Model Apr 2015 Kernel-Based Just-In-Time Learning for Passing Expectation Propagation Messages Feb 2012 Feature Selection via $\ell_1$-penalized Squared-loss Mutual Information

## Tea Talks

Tea talks I gave at Max Planck Institute for Intelligent Systems and at Gatsby Unit, UCL when I was a PhD student.

 Apr 2020 Integers and Divisibility May 2017 Exact String Matching with Z-Array Feb 2017 Some Counterexamples in Probability Oct 2016 Support Points Jul 2016 Least-Squares Two-Sample Test Dec 2015 9 Matlab Tricks that You Probably Want to Know Oct 2015 Optimal Dating Strategy Jul 2015 Support Vector Clustering May 2016 Useful Software/Tricks You Should Know Nov 2014 Public-key Cryptography with RSA Sep 2014 True Online TD$(\lambda)$ Jun 2014 Local Fisher Discriminant Analysis Apr 2014 Learning with Local and Global Consistency

## Machine Learning Journal Club

Talks I gave at the machine learning journal club at Gatsby Unit as a PhD student.

 Jan 2017 Examples are not Enough, Learn to Criticize! Criticism for Interpretability Oct 2016 Determinantal Point Processes for Machine Learning Feb 2016 Bayesian Indirect Inference Using a Parametric Auxiliary Model Nov 2015 On the High-dimensional Power of Linear-time Kernel Two-Sample Testing under Mean-shift Alternatives Aug 2015 Landmarking Manifolds with Gaussian Processes May 2015 Deep Exponential Families Apr 2015 Mean Field Methods Feb 2015 Sum-Product, Bethe Approximation