BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Talks.cam//talks.cam.ac.uk//
X-WR-CALNAME:Talks.cam
BEGIN:VEVENT
SUMMARY:Causal Modelling with Stationary Processes - Sarah Lumpp (Technica
 l University of Munich)
DTSTART:20260303T144500Z
DTEND:20260303T153000Z
UID:TALK244381@talks.cam.ac.uk
DESCRIPTION:Stationary distributions of multivariate diffusion processes h
 ave recently been proposed as probabilistic models of causal systems in st
 atistics and machine learning. By assuming each observation to arise as a 
 one-time cross-sectional snapshot of a temporal process in equilibrium\, t
 hey allow to model dependence structures that may include feedback loops. 
 Specifically\, the graphical continuous Lyapunov model consists of steady-
 state distributions of multivariate Ornstein-Uhlenbeck processes where spa
 rsity assumptions on the drift matrices are represented with a directed gr
 aph. These distributions are Gaussian with covariance matrices that are pa
 rametrized as solutions of the continuous Lyapunov equation. In this talk\
 , I will motivate the Lyapunov models and present the conditional independ
 ence structure as well as results on identifiability of the drift paramete
 rs in specific cases.&nbsp\;\n&nbsp\;
LOCATION:Seminar Room 1\, Newton Institute
END:VEVENT
END:VCALENDAR