15 citations · 16 across the 7 of their papers we have counts for
3 papers · 1 filter
Generative Intervention Models for Causal Perturbation Modeling
Nora Schneider, Lars Lorch, Niki Kilbertus +2
We consider the problem of predicting perturbation effects via causal models. In many applications, it is a priori unknown which mechanisms of a system are modified by an external…
Standardizing Structural Causal Models
Weronika Ormaniec, Scott Sussex, Lars Lorch +2
Synthetic datasets generated by structural causal models (SCMs) are commonly used for benchmarking causal structure learning algorithms. However, the variances and pairwise correla…
Causal Modeling with Stationary Diffusions
Lars Lorch, Andreas Krause, Bernhard Schölkopf
We develop a novel approach towards causal inference. Rather than structural equations over a causal graph, we learn stochastic differential equations (SDEs) whose stationary densi…