Creighton Heaukulani

I am a machine learning researcher at Goldman Sachs in Hong Kong.

My research interests are in probabilistic approaches to modeling and inference in all areas of modern statistics.

I completed my PhD in the Machine Learning Group at the University of Cambridge, under the supervision of Zoubin Ghahramani. I was previously supervised by Andrew R. Barron and Sekhar Tatikonda in the Statistics Department at Yale University.

Feel free to contact me at:
c [dot] k [dot] heaukulani [at] gmail.com



Publications

Bayesian inference on random simple graphs with power law degree distributions.
Juho Lee, C. Heaukulani, Zoubin Ghahramani, Lancelot F. James, and Seungjin Choi
Preprint. [paper]

Black-box constructions for exchangeable sequences of random multisets.
C. Heaukulani and Daniel M. Roy
Preprint available upon request.

Generalized IBPs, random multisets, and tree-structured feature allocations.
PhD Thesis.
University of Cambridge, Sept. 2016. [pdf]

Gibbs-type Indian buffet processes.
C. Heaukulani and Daniel M. Roy
Preprint. [paper]

Beta diffusion trees and hierarchical feature allocations.
C. Heaukulani, David A. Knowles, and Zoubin Ghahramani
ICML, 2014. Extended version: [paper][slides]

The combinatorial structure of beta negative binomial processes.
C. Heaukulani and Daniel M. Roy
Bernoulli, Vol. 22, No. 4, 2301--2324, 2016. [paper][slides]

Dynamic probabilistic models for latent feature propagation in social networks.
C. Heaukulani and Zoubin Ghahramani
ICML, 2013. [paper][slides]


Talks

Random partition based inference schemes for feature allocations.
BNP 10, Raleigh--Durham, June 2015 [slides]

Beta diffusion trees.
ICML 2014, Beijing, June 2014 [slides]

Probabilistic latent feature propagation in social networks.
ICML 2013, Atlanta, June 2013 [slides]
NetSci 2013 Satellite Symposium, Copenhagen, June 2013

The negative binomial IBP.
BNP 9, Amsterdam, March 2013 [slides]