Peng DingA First Course in CausalInferenceContents HYPERLINK l bookmark3 Preface xv HYPERLINK l bookmark4 Acronyms xvii
Texts in Statistical Science(共72册),这套丛书还有 《Bayesian Statistical Methods》《Practical Statistics for Medical Research》《Statistical Rethinking (2/e)》《Generalized Additive Models》《Stationary Stochastic Process》等。 喜欢读"A First Course in Causal Inference"的人也喜欢 ··· 社会科学研究...
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‘Intuitive physics’ enables our pragmatic engagement with the physical world and forms a key component of ‘common sense’ aspects of thought. Current artificial intelligence systems pale in their understanding of intuitive physics, in comparison to ev
domain adaptation by using causal inference to predict ... [Paper] domain adaptation with conditional distribution matching and ... [Paper] correcting covariate shift with the frank-wolfe algorithm [Paper] few-shot adaptation of pre-trained networks for domain shift [Paper] distance metric le...
Of course, we do not usually know an individual’s true infection status: rather, we have a set of diagnostic test results and from these we wish to infer the probability of an individual being infected. Here, we show how to do this in an approach where the parameters reflecting the ...
Causal inference in survival analysis using pseudo-observations. Stat Med. 2017;36(17):2669–81. Article PubMed Google Scholar Robins JM, Hernan MA, Brumback B. Marginal structural models and causal inference in epidemiology. Epidemiology. 2000;11(5):550–60. Article CAS PubMed Google Scholar...
19, 30, 31, 34 Whilst RCTs are at the upper end of the hierarchy of evidence in terms of causal inference regarding the efficacy or effectiveness of interventions, they cannot explore the complex nature of PA interventions in the school context.12 Insight into the key questions posed by ...
The causal inference framework based on DAGs discussed here provides an elegant and powerful theory of causality27,28(although it should be noted that alternative operationalizations exist30,71). It is closely related to the notion ofintervention(as described in Section 2.3.2), the idea that we...
The ability to generalize well is one of the primary desiderata for models of natural language processing (NLP), but what ‘good generalization’ entails and how it should be evaluated is not well understood. In this Analysis we present a taxonomy for ch