45 citations · 126 across the 21 of their papers we have counts for
22 papers
Scalable partial information decomposition for symptom networks via supervised embeddings
Cillian Hourican, Eric Dignum, Rick Quax +1
Pairwise relationships among mental-health symptoms are routinely summarised asscalar edge weights, which cannot express whether two symptoms carry overlapping information about a…
Resilience of coupled systems under deep uncertainty and dynamic complexity: An integrative literature review
Jannie Coenen, Vítor Vasconcelos, Heiman Wertheim +8
Resilience in coupled systems is increasingly critical in addressing global challenges such as climate change and pandemics. These systems show unpredictable behaviour due to dynam…
Diagrams-to-Dynamics (D2D): Exploring Causal Loop Diagram Leverage Points under Uncertainty
Jeroen F. Uleman, Loes Crielaard, Leonie K. Elsenburg +4
Background: Causal loop diagrams (CLDs) are widely used in health and environmental research to represent hypothesized causal structures underlying complex problems. However, as qu…
Multilayer Network of Cardiovascular Diseases and Depression via Multipartite Projection
Jie Li, Cillian Hourican, Pashupati P. Mishra +10
Cardiovascular diseases (CVD) and depression exhibit significant comorbidity, which is highly predictive of poor clinical outcomes. Yet, the underlying biological pathways remain c…
Abstract Markov Random Fields
Leon Lang, Clélia de Mulatier, Rick Quax +1
Markov random fields are known to be fully characterized by properties of their information diagrams, or I-diagrams. In particular, for Markov random fields, regions in the I-diagr…
Towards participatory multi-modeling for policy support across domains and scales: a systematic procedure for integral multi-model design
Vittorio Nespeca, Rick Quax, Marcel G. M. Olde Rikkert +9
Policymaking for complex challenges such as pandemics necessitates the consideration of intricate implications across multiple domains and scales. Computational models can support…