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  • 标题:Reasoning with Conditional Probabilities and Joint Distributions in Coq
  • 其他标题:Reasoning with Conditional Probabilities and Joint Distributions in Coq
  • 本地全文:下载
  • 作者:AFFELDT Reynald ; GARRIGUE Jacques ; SAIKAWA Takafumi
  • 期刊名称:コンピュータ ソフトウェア
  • 印刷版ISSN:0289-6540
  • 出版年度:2020
  • 卷号:37
  • 期号:3
  • 页码:3_79-3_95
  • DOI:10.11309/jssst.37.3_79
  • 出版社:Japan Society for Software Science and Technology
  • 摘要:Probabilities occur in many applications of computer science, such as communication theory and artificial intelligence. These are critical applications that require some form of verification to guarantee the quality of their implementations. Unfortunately, probabilities are also the typical example of a mathematical theory whose abuses of notations make pencil-and-paper proofs difficult to formalize. In this paper, we experiment a new formalization of conditional probabilities that we validate with two applications. First, we formalize the foundational definitions and theorems of information theory, extending previous work with new lemmas. Second, we formalize the notion of conditional independence and its properties, paving the road for a formalization of probabilistic graphical models.
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