Identifying causal effects via context-specific independence relations
Causal effect identification considers whether an interventional probability distribution can
be uniquely determined from a passively observed distribution in a given causal structure. If …
be uniquely determined from a passively observed distribution in a given causal structure. If …
Probabilistic team semantics
Team semantics is a semantical framework for the study of dependence and independence
concepts ubiquitous in many areas such as databases and statistics. In recent works team …
concepts ubiquitous in many areas such as databases and statistics. In recent works team …
Team semantics for interventionist counterfactuals: observations vs. interventions
F Barbero, G Sandu - Journal of Philosophical Logic, 2021 - Springer
Team semantics is a highly general framework for logics which describe dependencies and
independencies among variables. Typically, the (in) dependencies considered in this …
independencies among variables. Typically, the (in) dependencies considered in this …
Learning and interpreting asymmetry-labeled DAGs: a case study on COVID-19 fear
M Leonelli, G Varando - Applied Intelligence, 2024 - Springer
Bayesian networks are widely used to learn and reason about the dependence structure of
discrete variables. However, they can only formally encode symmetric conditional …
discrete variables. However, they can only formally encode symmetric conditional …
Approximation and dependence via multiteam semantics
We define a variant of team semantics called multiteam semantics based on multisets and
study the properties of various logics in this framework. In particular, we define natural …
study the properties of various logics in this framework. In particular, we define natural …
Descriptive complexity of real computation and probabilistic independence logic
We introduce a novel variant of BSS machines called Separate Branching BSS machines (S-
BSS in short) and develop a Fagin-type logical characterisation for languages decidable in …
BSS in short) and develop a Fagin-type logical characterisation for languages decidable in …
Facets of distribution identities in probabilistic team semantics
We study probabilistic team semantics which is a semantical framework allowing the study of
logical and probabilistic dependencies simultaneously. We examine and classify the …
logical and probabilistic dependencies simultaneously. We examine and classify the …
Staged trees and asymmetry-labeled DAGs
G Varando, F Carli, M Leonelli - Metrika, 2024 - Springer
Bayesian networks are a widely-used class of probabilistic graphical models capable of
representing symmetric conditional independence between variables of interest using the …
representing symmetric conditional independence between variables of interest using the …
Linear-time temporal logic with team semantics: Expressivity and complexity
We study the expressivity and complexity of model checking linear temporal logic with team
semantics (TeamLTL). TeamLTL, despite being a purely modal logic, is capable of defining …
semantics (TeamLTL). TeamLTL, despite being a purely modal logic, is capable of defining …
Complexity of propositional logics in team semantic
We classify the computational complexity of the satisfiability, validity, and model-checking
problems for propositional independence, inclusion, and team logic. Our main result shows …
problems for propositional independence, inclusion, and team logic. Our main result shows …