9 citations · 12 across the 6 of their papers we have counts for
6 papers
Federated Causal Discovery via Regression-Directed Cumulants
Pablo Torrijos, Fabio Stella, José A. Gámez +1
In this paper we study linear non-Gaussian acyclic models (LiNGAM) when used in federated environments. These causal models allow one to go beyond Markov equivalence. However, in m…
On the Relationship between Bayesian Networks and Probabilistic Structural Causal Models
Peter J. F. Lucas, Eleonora Zullo, Fabio Stella
In this paper, the relationship between probabilistic graphical models, in particular Bayesian networks, and causal diagrams, also called structural causal models, is studied. Stru…
Causal Discovery on Higher-Order Interactions
Alessio Zanga, Marco Scutari, Fabio Stella
Causal discovery combines data with knowledge provided by experts to learn the DAG representing the causal relationships between a given set of variables. When data are scarce, bag…
The Importance of Causality in Decision Making: A Perspective on Recommender Systems
Emanuele Cavenaghi, Alessio Zanga, Fabio Stella +1
Causality is receiving increasing attention in the Recommendation Systems (RSs) community, which has realised that RSs could greatly benefit from causality to transform accurate pr…
Causal Discovery in Recommender Systems: Example and Discussion
Emanuele Cavenaghi, Fabio Stella, Markus Zanker
Causality is receiving increasing attention by the artificial intelligence and machine learning communities. This paper gives an example of modelling a recommender system problem u…
Towards a Transportable Causal Network Model Based on Observational Healthcare Data
Alice Bernasconi, Alessio Zanga, Peter J. F. Lucas +2
Over the last decades, many prognostic models based on artificial intelligence techniques have been used to provide detailed predictions in healthcare. Unfortunately, the real-worl…