EXERT
发表于 2025-3-21 18:14:13
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deface
发表于 2025-3-21 20:52:11
https://doi.org/10.1007/978-3-031-35051-1Causality; Counterfactuals; Treatment Effect Estimation; Causal Discovery; statistics
强壮
发表于 2025-3-22 02:09:42
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cunning
发表于 2025-3-22 08:36:40
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absolve
发表于 2025-3-22 09:10:47
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传授知识
发表于 2025-3-22 15:50:23
Overview of the BookThis chapter briefly introduces the general concepts of machine learning and causal inference, discusses their connections, and then presents the organization of this book. The research topic of each chapter is also briefly described to serve as a road map of the book.
d-limonene
发表于 2025-3-22 19:48:49
SummaryThis chapter summarizes this book and highlights research challenges and future opportunities on the topic of machine learning for causal inference.
漂泊
发表于 2025-3-22 21:54:21
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ARIA
发表于 2025-3-23 04:06:34
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独轮车
发表于 2025-3-23 07:31:23
and interpretability challenges posed by conventional ML metThis book provides a deep understanding of the relationship between machine learning and causal inference. It covers a broad range of topics, starting with the preliminary foundations of causal inference, which include basic definitions, il