Continuous causal structure learning from incremental instances and feature spaces

Author:

You DianlongORCID,Wu Hongtao,Liu Jiale,Yan Huigui,Ma Chuan,Chen Zhen,Wu Xindong

Publisher

Elsevier BV

Subject

Hardware and Architecture,Information Systems,Signal Processing,Software

Reference48 articles.

1. Causal structure learning: A combinatorial perspective;Squires;Found. Comput. Math.,2022

2. F. Zhou, K. He, Y. Ni, Causal Discovery with Heterogeneous Observational Data, in: Proceedings of the 38th Conference on Uncertainty in Artificial Intelligence, UAI, 2022, pp. 2383–2393.

3. J. Pensar, T. Talvitie, A. Hyttinen, M. Koivisto, A Bayesian approach for estimating causal effects from observational data, in: Proceedings of AAAI 2020 34th AAAI Conference on Artificial Intelligence, 2020, pp. 5395–5402.

4. L. Wang, M. Chignell, H. Jiang, S. Lokuge, G. Mason, K. Fotinos, M. Katzman, Discovering the causal structure of the Hamilton rating scale for depression using causal discovery, in: Proceedings of 2021 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI, 2021, pp. 1–4.

5. Examining the Impact of Neanderthal DNA on Modern Human Biology;Robles,2022

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