Publisher
Springer Nature Switzerland
Reference10 articles.
1. Glymour, C., Zhang, K., Spirtes, P.: Review of causal discovery methods based on graphical models. Front. Genet. 10, 524 (2019). https://doi.org/10.3389/fgene.2019.00524
2. Quintana, R.: The structure of academic achievement: searching for proximal mechanisms using causal discovery algorithms. Sociol. Methods Res. 52(1), 85–134 (2023). https://doi.org/10.1177/0049124120926208
3. Chen, H., Du, K., Yang, X., Li, C.: A review and roadmap of deep learning causal discovery in different variable paradigms. ArXiv abs/2209.06367 (2022)
4. Schölkopf, B., von Kügelgen, J.: From statistical to causal learning. arXiv preprint arXiv:2204.00607 (2022)
5. Upadhyaya, P., Zhang, K., Li, C., Jiang, X., Kim, Y.: Scalable causal structure learning: scoping review of traditional and deep learning algorithms and new opportunities in biomedicine. JMIR Med. Inform. (2023). https://doi.org/10.2196/38266