45 citations · 126 across the 21 of their papers we have counts for
3 papers · 1 filter
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…
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…
Learning Lie Group Symmetry Transformations with Neural Networks
Alex Gabel, Victoria Klein, Riccardo Valperga +4
The problem of detecting and quantifying the presence of symmetries in datasets is useful for model selection, generative modeling, and data analysis, amongst others. While existin…