Variational inference (VI) plays an essential role in approximate Bayesian inference due to its computational efficiency and broad applicability. Crucial to the performance of VI is the selection of ...

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由Joshua D. Angrist和Jörn-Steffen Pischke合作撰写的计量经济学经典著作Mostly Harmless Econometrics: An Empiricist's Companion详细介绍了应用实证研究中的核心计量工具，为社会科学研究者提供了一份精炼的操作指南。 作者从因果关系及其识别的角度展开了本书的论述。对于社会 ...

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Abstract: Many modern unsupervised or semi-supervised machine learning algorithms rely on Bayesian probabilistic models. These models are usually intractable and thus require approximate inference.

Abstract: In this article, the unsupervised domain adaptation problem, where an approximate inference model is to be learned from a labeled dataset and expected to generalize well on an unlabeled ...

Dynamical systems theory provides a mathematical framework for studying how complex systems evolve over time, such as the neurons in our brains, the global climate system, or engineered cells. But ...

"description": "PyData DC 2016\n\nJupyter notebook: https://nbviewer.jupyter.org/gist/AustinRochford/91cabfd2e1eecf9049774ce529ba4c16\n\nInference in Bayesian models ...

Due to a planned power outage on Friday, 1/14, between 8am-1pm PST, some services may be impacted. A line drawing of the Internet Archive headquarters building façade. An illustration of a magnifying ...