4 papers
Fine asymptotics for approximate simulation of symmetric channels
Valentinian Lungu, Aaron B. Wagner, Ioannis Kontoyiannis
We study the approximate channel simulation problem in the normal approximation regime. Our starting point is the fact established by Cao et al.~\cite{Cao_channel_simulation}, that…
The relative value of interventional and observational samples in Bayesian Causal Linear Gaussian Models
Valentinian Lungu, Anish Dhir, Mark van der Wilk +1
We investigate the asymptotic properties of Bayesian bivariate causal discovery for Gaussian Linear Structural Equation Models (SEMs) with heteroscedastic noise. We demonstrate tha…
Bayesian causal discovery: Posterior concentration and optimal detection
Valentinian Lungu, Joni Shaska, Ioannis Kontoyiannis +1
We consider the problem of Bayesian causal discovery for the standard model of linear structural equations with equivariant Gaussian noise. A uniform prior is placed on the space o…
Estimating Interventional Distributions with Uncertain Causal Graphs through Meta-Learning
Anish Dhir, Cristiana Diaconu, Valentinian Mihai Lungu +3
In scientific domains -- from biology to the social sciences -- many questions boil down to \textit{What effect will we observe if we intervene on a particular variable?} If the ca…