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Datasets are growing not just in size but in complexity, creating a demand for rich models and quantification of uncertainty. Bayesian methods are an excellent fit for this demand, but scaling Bayesian inference is a challenge. In response to this challenge, there has been considerable recent work based on varying assumptions about model structure, underlying computational resources, and the importance of asymptotic correctness. As a result, there is a zoo of ideas with a wide range of assumptions and applicability. Patterns of Scalable Bayesian Inference seeks to identify unifying...

Visualizing Modern China: Image, History, and Memory, 1750-Present offers a sophisticated yet accessible interpretation of modern Chinese history through visual imagery. With rich illustrations and a companion website, it is an ideal textbook for college-level courses on modern Chinese history and on modern visual culture. The introduction provides a methodological framework and historical overview, while the chronologically arranged chapters use engaging case studies to explore important themes. Topics include: Qing court ritual, rebellion and war, urban/rural relations, art and...