Causal inference methods for supporting, understanding, and improving decision-making
<p>Causality and the ability to reason about cause-and-effect relationships are central to decision-making. This thesis contributes to the area of causal inference by proposing new machine learning methods that can be used for supporting, understanding, and improving decision-making, with a fo...
主要作者: | Bica, I |
---|---|
其他作者: | van der Schaar, M |
格式: | Thesis |
语言: | English |
出版: |
2022
|
主题: |
相似书籍
-
Interpretable causal systems: interpretability and causality in machine learning for human and nonhuman decision-making
由: Graham, L
出版: (2020) -
Large scale methods for kernels, causal inference and survival modelling
由: Hu, R
出版: (2022) -
Causal ML: Python package for causal inference machine learning
由: Yang Zhao, et al.
出版: (2023-02-01) -
Deep learning for causal inference on electronic health records
由: Rao, S
出版: (2023) -
Causal evidence in health decision making: methodological approaches of causal inference and health decision science
由: Kühne, Felicitas, et al.
出版: (2022-12-01)