Amortized inference and model learning for probabilistic programming
<p>Probabilistic modeling lets us infer, predict and make decisions based on incomplete or noisy data. The goal of <em>probabilistic programming</em> is to automate inference in probabilistic models that are expressed as probabilistic programs---programs that can draw random values...
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| 格式: | Thesis |
| 语言: | English |
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2019
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