17 citations · 33 across the 10 of their papers we have counts for
11 papers
Evaluation of A National Digitally-Enabled Health Promotion Campaign for Mental Health Awareness using Social Media Platforms Tik Tok, Facebook, Instagram, and YouTube
Samantha Bei Yi Yan, Dinesh Visva Gunasekeran, Caitlyn Tan +7
Mental health disorders rank among the 10 leading contributors to the global burden of diseases, yet persistent stigma and care barriers delay early intervention. This has inspired…
A Multi-Agent Dual Dialogue System to Support Mental Health Care Providers
Onno P. Kampman, Ye Sheng Phang, Stanley Han +9
We introduce a general-purpose, human-in-the-loop dual dialogue system to support mental health care professionals. The system, co-designed with care providers, is conceptualized t…
Modelling financial volume curves with hierarchical Poisson processes
Creighton Heaukulani, Abhinav Pandey, Lancelot F. James
Modeling the trading volume curves of financial instruments throughout the day is of key interest in financial trading applications. Predictions of these so-called volume profiles…
HOPES -- An Integrative Digital Phenotyping Platform for Data Collection, Monitoring and Machine Learning
Xuancong Wang, Nikola Vouk, Creighton Heaukulani +4
We describe the development of, and early experiences with, comprehensive Digital Phenotyping platform: Health Outcomes through Positive Engagement and Self-Empowerment (HOPES). HO…
Black-box constructions for exchangeable sequences of random multisets
Creighton Heaukulani, Daniel M. Roy
We develop constructions for exchangeable sequences of point processes that are rendered conditionally-i.i.d. negative binomial processes by a (possibly unknown) random measure cal…
Scalable Bayesian dynamic covariance modeling with variational Wishart and inverse Wishart processes
Creighton Heaukulani, Mark van der Wilk
We implement gradient-based variational inference routines for Wishart and inverse Wishart processes, which we apply as Bayesian models for the dynamic, heteroskedastic covariance…
Variational inference for neural network matrix factorization and its application to stochastic blockmodeling
Onno Kampman, Creighton Heaukulani
We consider the probabilistic analogue to neural network matrix factorization (Dziugaite & Roy, 2015), which we construct with Bayesian neural networks and fit with variational inf…
Bayesian inference on random simple graphs with power law degree distributions
Juho Lee, Creighton Heaukulani, Zoubin Ghahramani +2
We present a model for random simple graphs with a degree distribution that obeys a power law (i.e., is heavy-tailed). To attain this behavior, the edge probabilities in the graph…
Gibbs-type Indian buffet processes
Creighton Heaukulani, Daniel M. Roy
We investigate a class of feature allocation models that generalize the Indian buffet process and are parameterized by Gibbs-type random measures. Two existing classes are containe…
Beta diffusion trees and hierarchical feature allocations
Creighton Heaukulani, David A. Knowles, Zoubin Ghahramani
We define the beta diffusion tree, a random tree structure with a set of leaves that defines a collection of overlapping subsets of objects, known as a feature allocation. A genera…
The combinatorial structure of beta negative binomial processes
Creighton Heaukulani, Daniel M. Roy
We characterize the combinatorial structure of conditionally-i.i.d. sequences of negative binomial processes with a common beta process base measure. In Bayesian nonparametric appl…