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Zihuai Zeng

2 accepted papers

2026

On the Identifiability of Poisson Branching Structural Causal Model Under Latent Confounding

ICML 2026oral

Causal discovery from observational count data poses unique challenges, particularly when the data exhibit inherent branching structures, e.g., an upstream event (e.g., an ad impression) triggers a downstream event (e.g., a purchase) with a certain probability. Such branching dynamics are naturally …

Cited by 0SourceScholar
2024

On the Identifiability of Poisson Branching Structural Causal Model Using Probability Generating Function

NeurIPS 2024spotlight

Causal discovery from observational data, especially for count data, is essential across scientific and industrial contexts, such as biology, economics, and network operation maintenance. For this task, most approaches model count data using Bayesian networks or ordinal relations. However, they over…

Cited by 0SourcePDFScholar