This paper addresses intervention-based causal representation learning (CRL) under a
general nonparametric latent causal model and an unknown transformation that maps the …

We consider the linear causal representation learning setting where we observe a linear
mixing of $ d $ unknown latent factors, which follow a linear structural causal model. Recent …

Despite the multifaceted recent advances in interventional causal representation learning
(CRL), they primarily focus on the stylized assumption of single-node interventions. This …

The focus of this dissertation is leveraging the interventions in causal learning. Directed
acyclic graphs (DAGs) have been used to compactly represent cause-effect relationships …

Consider a data-generation process that transforms low-dimensional _latent_ causally-
related variables to high-dimensional _observed_ variables. Causal representation learning …

Score-based CRL from Interventions Page 1 Score-based CRL from Interventions Burak
Varıcı Rensselaer Polytechnic Institute Emre Acartürk (RPI) Karthikeyan Shanmugam (Google) …