Christopher Lohse, Adrian Selk, et al.
NeurIPS 2025
The use of a hypothetical generative model was been suggested for causal analysis of observa- tional data. The very assumption of a particular model is a commitment to a certain set of variables and therefore to a certain set of possible causes. Estimating the joint probability distribution of can be useful for predicting values of variables in view of the observed values of others, but it is not sufficient for inferring causal relationships. The model describes a single observable distribution and cannot a chain of effects of intervention that deviate from the observed distribution.
Christopher Lohse, Adrian Selk, et al.
NeurIPS 2025
Dirk Fahland, Fabiana Fournier, et al.
DKE
Kohei Miyaguchi, Masao Joko, et al.
ASMC 2025
Naiyu Yin, Hanjing Wang, et al.
NeurIPS 2023