7 citations · 11 across the 10 of their papers we have counts for
10 papers
Learning from data with structured missingness
Robin Mitra, Sarah F. McGough, Tapabrata Chakraborti +17
Missing data are an unavoidable complication in many machine learning tasks. When data are `missing at random' there exist a range of tools and techniques to deal with the issue. H…
Where the Bee Sucks -- A Dynamic Bayesian Network Approach to Decision Support for Pollinator Abundance Strategies
Martine J. Barons, Aditi Shenvi
For policymakers wishing to make evidence-based decisions, one of the challenges is how to combine the relevant information and evidence in a coherent and defensible manner in orde…
cegpy: Modelling with Chain Event Graphs in Python
Gareth Walley, Aditi Shenvi, Peter Strong +1
Chain event graphs (CEGs) are a recent family of probabilistic graphical models that generalise the popular Bayesian networks (BNs) family. Crucially, unlike BNs, a CEG is able to…
Beyond Conjugacy for Chain Event Graph Model Selection
Aditi Shenvi, Silvia Liverani
Chain event graphs are a family of probabilistic graphical models that generalise Bayesian networks and have been successfully applied to a wide range of domains. Unlike Bayesian n…
Score Equivalence for Staged Trees
Conor Hughes, Peter Strong, Aditi Shenvi
Staged trees are a recently-developed, powerful family of probabilistic graphical models. An equivalence class of staged trees has now been characterised, and two fundamental stati…
Building A Bayesian Decision Support System for Evaluating COVID-19 Countermeasure Strategies
Peter Strong, Aditi Shenvi, Xuewen Yu +3
Decision making in the face of a disaster requires the consideration of several complex factors. In such cases, Bayesian multi-criteria decision analysis provides a framework for d…
A Bayesian decision support system for counteracting activities of terrorist groups
Aditi Shenvi, F. Oliver Bunnin, Jim Q. Smith
Activities of terrorist groups present a serious threat to the security and well-being of the general public. Counterterrorism authorities aim to identify and frustrate the plans o…
Propagation for Dynamic Continuous Time Chain Event Graphs
Aditi Shenvi, Jim Q. Smith
Chain Event Graphs (CEGs) are a family of event-based graphical models that represent context-specific conditional independences typically exhibited by asymmetric state space probl…
Constructing a Chain Event Graph from a Staged Tree
Aditi Shenvi, Jim Q. Smith
Chain Event Graphs (CEGs) are a recent family of probabilistic graphical models - a generalisation of Bayesian Networks - providing an explicit representation of structural zeros,…
A Bayesian Dynamic Graphical Model for Recurrent Events in Public Health
Aditi Shenvi, Jim Q. Smith
To analyze the impacts of certain types of public health interventions we need to estimate the treatment effects and outcomes as these apply to heterogeneous open populations. Dyna…