Causal Discovery with Linear Non-Gaussian Models under Measurement Error: Structural Identifiability Results
By Kun Zhang, Mingming Gong, J. Ramsey, Kayhan Batmanghelich, Peter Spirtes, Clark Glymour. 2018
27 citations recorded by the source corpus.
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Stefan Bauer
- Niklas Pfister
- Bernhard Schölkopf
- Francesco Locatello
- Jan Peters
- Yoshua Bengio
- Anirudh Goyal
Citations in the corpus
- Causal Models for Dynamical Systems (2020, methodology): “2006] and an increased difficulty when identifying parameters or causal structure from data [Zhang et al. 2018].”
- A survey of Bayesian Network structure learning (2021, unknown): “Zhang et al. (2018) investigated the identifiability conditions for Linear Non-Gaussian Models in the presence of measurement error.”