Diffusion-based graph generative models have recently obtained promising results for graph
generation. However, existing diffusion-based graph generative models are mostly one-shot …

Healthcare-associated infections (HAIs) are a major problem in hospital infection control.
Although HAIs can be suppressed using contact precautions, such precautions are …

The global world had recently observed a set of computational paradigm shift characterised
by Internet of Things (IoTs), Internet of Health Things (IoHTs), Innovative Internet of 5G …

Graph diffusion models have emerged as state-of-the-art techniques in graph generation,
yet integrating domain knowledge into these models remains challenging. Domain …

Given a large, semi-infinite collection of co-evolving epidemiological data containing the
daily counts of cases/deaths/recovered in multiple locations, how can we incrementally …

We consider the task of estimating a network cascade as fast as possible. The cascade is
assumed to spread according to a general Susceptible-Infected process with heterogeneous …

Healthcare acquired infections (HAIs)(eg, Methicillin-resistant Staphylococcus aureus
infection) have complex transmission pathways, spreading not just via direct person-to …

This paper studies the problem of detecting asymptomatic cases in a temporal contact
network in which multiple outbreaks have occurred. We show that the key to detecting …

We study the polyhedral convex hull structure of a mixed-integer set which arises in a class
of cardinality-constrained concave submodular minimization problems. This class of …

Continual learning has emerged as a powerful approach to address the challenges of non-
stationary environments, allowing machine learning models to adapt to new data while …