Causal Representation Learning

Linear Causal Disentanglement via Interventions

Causal disentanglement seeks a representation of data involving latent variables that relate to one another via a causal model. A …

Chandler Squires, Anna Seigal, Salil Bhate, Caroline Uhler

Identifiability Guarantees for Causal Disentanglement from Soft Interventions

Causal disentanglement aims to uncover a representation of data using latent variables that are interrelated through a causal model. …

Jiaqi Zhang, Chandler Squires, Kristjan Greenewald, Akash Srivastava, Karthikeyan Shanmugam, Caroline Uhler

Unpaired Multi-Domain Causal Representation Learning

The goal of causal representation learning is to find a representation of data that consists of causally related latent variables. We …

Nils Sturma, Chandler Squires, Mathias Drton, Caroline Uhler