Talks

From a 3,000-person NeurIPS tutorial on comparing distributions and models, to invited research talks, to tea-talks and journal-club sessions given as a postdoc and PhD student.

Tutorials

Dec 2019
NeurIPS 2019 Tutorial: Interpretable Comparison of Distributions and Models
Video.
Slides (part 1, part 2, part 3).
3000+ people in the live audience.
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, Thailand.

Research

11 Oct 2019
Informative Features for Model Comparison
Sep 2019
Informative Features for Comparing Distributions
Feb 2018
A Linear-Time Kernel Goodness-of-Fit Test
June 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 L1-penalized Squared-loss Mutual Information

Tea Talks

Given at the Max Planck Institute for Intelligent Systems as a postdoc, and at the Gatsby Unit, UCL as a PhD student — short, often playful talks beyond core research.

9 April 2020
Integers and Divisibility
May 2017
Exact String Matching with Z-Array
Feb 2017
Some Counterexamples in Probability
Oct 2016
Support Points
July 2016
Least-Squares Two-Sample Test
Dec 2015
9 Matlab Tricks that You Probably Want to Know
Oct 2015
Optimal Dating Strategy
July 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

ML Journal Club

Talks given at the machine learning journal club at the Gatsby Unit, UCL 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