3 papers - avg viability 4.0
A generative framework for learning interpretable causal relationships among discrete latent variables from complex observational data.
A framework for improving causal representation learning through enhanced dataset evaluation and reproducibility.
A theoretical framework for estimating causal representations from multi-domain data using empirical Bayes.