Name
Abstract | ||
|---|---|---|
Structural Causal Models are widely used in causal modelling, but how they relate to other modelling tools is poorly understood. In this paper we provide a novel perspective on the relationship between Ordinary Differential Equations and Structural Causal Models. We show how, under certain conditions, the asymptotic behaviour of an Ordinary Differential Equation under non-constant interventions can be modelled using Dynamic Structural Causal Models. In contrast to earlier work, we study not only the effect of interventions on equilibrium states; rather, we model asymptotic behaviour that is dynamic under interventions that vary in time, and include as a special case the study of static equilibria. |
Year | Venue | DocType |
|---|---|---|
2018 | uncertainty in artificial intelligence | Conference |
Volume | Citations | PageRank |
abs/1608.08028 | 1 | 0.38 |
References | Authors | |
6 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Paul Rubenstein | 1 | 11 | 4.28 |
| Stephan Bongers | 2 | 3 | 2.49 |
| Joris M. Mooij | 3 | 679 | 50.48 |
| bernhard schoelkopf | 4 | 7 | 0.82 |