Researcher Portfolio
Huang, Biwei
Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society
Researcher Profile
Position: Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society
Researcher ID: https://pure.mpg.de/cone/persons/resource/persons147474
Publications
: Huang, B. (2022). Learning and Using Causal Knowledge: A Further Step Towards a Higher-Level Intelligence. PhD Thesis, Carnegie Mellon University, Pittsburgh, PA. [PubMan] : Huang, B., Zhang, K., Zhang, J., Sanchez-Romero, R., Glymour, C., & Schölkopf, B. (2017). Behind Distribution Shift: Mining Driving Forces of Changes and Causal Arrows. In 2017 IEEE International Conference on Data Mining (ICDM 2017) (pp. 913-918). Piscataway, NJ, USA: IEEE. doi:10.1109/ICDM.2017.114. [PubMan] : Zhang, K., Zhang, J., Huang, B., Schölkopf, B., & Glymour, C. (2016). On the Identifiability and Estimation of Functional Causal Models in the Presence of Outcome-Dependent Selection. In A. Ihler, & D. Janzing (Eds. ), 32nd Conference on Uncertainty in Artificial Intelligence 2016 (pp. 825-834). Red Hook, NY: Curran Associates, Inc. Retrieved from http://dl.acm.org/citation.cfm?id=3020948.3021033. [PubMan] : Huang, B., Zhang, K., & Schölkopf, B. (2015). Identification of Time-Dependent Causal Model: A Gaussian Process Treatment. In Y. Qiang, & W. Michael (Eds. ), International Joint Conference on Artificial Intelligence, Machine Learning Track (pp. 3561-3568). Palo Alto, California, USA: AAAI Press. [PubMan] : Huang, B. (2014). Causal Discovery in the Presence of Time-Dependent Relations or Small Sample Size. Diploma Thesis, Universität Tübingen, Tübingen. [PubMan]