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This volume in the Challenges in Machine Learning series gathers papers from the Mini Symposium on Causality in Time Series, which was part of the Neural Inform
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This book presents ground-breaking advances in the domain of causal structure learning. The problem of distinguishing cause from effect (“Does altitude cause
An Introduction to Causal Inference
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Authors: Judea Pearl
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This paper summarizes recent advances in causal inference and underscores the paradigmatic shifts that must be undertaken in moving from traditional statistical
Elements of Causal Inference
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Authors: Jonas Peters
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A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning. The mathematization of causality is
The Book of Why
Language: en
Pages: 432
Authors: Judea Pearl
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Type: BOOK - Published: 2018-05-15 - Publisher: Basic Books

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A Turing Award-winning computer scientist and statistician shows how understanding causality has revolutionized science and will revolutionize artificial intell