3 accepted papers
Real-world networks grow over time; statistical models based on node exchangeability are not appropriate. Instead of constraining the structure of the *distribution* of edges, we propose that the relevant symmetries refer to the *causal structure* between them. We first enumerate the 96 causal direc
By relaxing conditions for {“}natural{”} structure learning algorithms, a family of constraint-based algorithms containing all exact structure learning algorithms under the faithfulness assumption, we define localised natural structure learning algorithms (LoNS). We also provide a set of necessary a…
Determinantal point processes (DPPs) are probabilistic models for repulsion. When used to represent the occurrence of random subsets of a finite base set, DPPs allow to model global negative associations in a mathematically elegant and direct way. Discrete DPPs have become popular and computationall…