What is the translation of " 贝叶斯推理 " in English?

• bayesian inference
• bayesian reasoning

Examples of using 贝叶斯推理 in Chinese and their translations into English

贝叶斯推理.
Bayesian Inference.

贝叶斯推理和机器学习（BayesianReasoningandMachineLearning）byDavidBarberWEB.
Bayesian Reasoning and Machine Learning, by David Barber.

贝叶斯推理和证据累积，是人工智能（2）的基础计算，也是人类基本的无意识机制。
Bayesian inference and evidence accumulation, which are cornerstone computations for AI(2), are basic unconscious mechanisms for humans.

概率和贝叶斯推理是我们理解机器学习首要的理论支柱之一。
Probabilistic and Bayesian reasoning is one of the principle theoretical pillars to our understanding of machine learning.

贝叶斯分析方法有很多名称，“贝叶斯推理”、“逆概率”、“贝叶斯更新”….
Bayesian analysis can go by many names,‘Bayesian Inference',‘Inverse Probability',‘Bayesian Updating'….

但这个定理--或实际上是构成其基础的「贝叶斯推理」这个思想--无处不在。
But the theorem- or really, the idea of“Bayesian reasoning” that underlies it- is ubiquitous.

NET是一个在图形模型中运行贝叶斯推理的框架，它也可以用于概率编程。
NET is a framework for running Bayesian inference in graphical models that can also be used for probabilistic programming.

而贝叶斯推理是此方式的数学实现形式，得益于此，我们可以做出更加精确的预测。
Bayesian inference is a way to capture this in math so that we can make more accurate predictions.

有几次我尝试着学习MCMC和贝叶斯推理，我每次从阅读书籍开始，结果却很快放弃。
Several times I tried to learn MCMC and Bayesian inference, but every time I started reading the books, I soon gave up.

斯坦是一个专门的程序，执行贝叶斯推理，是一种基于概率理论，合并来自多个源的信息的方法。
Stan is a specialized program that performs Bayesian inference, which is an approach, based on probability theory, for combining information from multiple sources.

事实上，人类并不是很擅长贝叶斯推理，至少在牵涉到语言推理时是这样的。
Humans, it turns out, are not very good at Bayesian inference, at least when verbal reasoning is involved.

在此，我们展示如何使用概率编程和贝叶斯推理来轻松构建工具，更好地预测更有效的决策。
Here, we show how to use probabilistic programming and Bayesian inference to easily build tools that make better predictions for more effective decision making.

贝叶斯推理同时考虑新证据的力量和已有假设的力量。
Bayesian inference considers both the strength of new evidence and the strength of your existing hypotheses.

实质上，每当你做某种形式的数值优化时，你都会用特定的假设和先验来执行一些贝叶斯推理。
In essence, every time that you do some form of numerical optimization, you're performing some Bayesian inference with particular assumptions and priors.

我们可以用医学诊断中的一个例子来阐明，也就是贝叶斯推理的“杀手级应用”之一。
We can illustrate it with an example from medical diagnosis, one of the“killer apps” of Bayesian inference.

它是一个怪物，今天治理三个最有力的思想在科学︰贝叶斯推理、开放源码软件和重复性研究。
And it's a monster, harnessing three of the most powerful ideas in science today: Bayesian inference, open-source software, and reproducible research.

要在Python中实现MCMC，我们需要使用PyMC3贝叶斯推理库。
To implement MCMC in Python, we will use the PyMC3 Bayesian inference library.

本质上讲，每次当你做某些形式的数运算，你就在使用特定假设和prior执行一些贝叶斯推理方程。
In essence, every time that you do some form of numerical optimization, you're performing some Bayesian inference with particular assumptions and priors.

我最喜欢的一个是将该方法阐释为贝叶斯推理执行的一部分。
One of my favorites is the interpretation of the methods as part of performing Bayesian inference.

事实证明，人类并不是很擅长贝叶斯推理，至少涉及文字推理的时候是这样的。
Humans, it turns out, are not very good at Bayesian inference, at least when verbal reasoning is involved.

然而，大多数图书讨论贝叶斯推理，依赖于非常复杂的数学分析和人工的例子，使没有强大数学背景的人无法接触。
However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background.

尽管蒙特卡洛模拟可以帮助解决贝叶斯推理所需的许多难解积分，但即使这些方法在计算上也非常昂贵。
While Monte Carlo simulations can help solve many intractable integrals needed for Bayesian inference, even these methods can be very computationally expensive.

同时，使用贝叶斯推理框架，来提供模型参数的估计以及对带有不确定性度量的预测。
Secondly, Bayesian inferential framework allows providing estimates of model parameters and forecasts with measures of uncertainty.

贝叶斯推理的方法非常自然和极其强大。
Bayesian methods of inference are deeply natural and extremely powerful.

贝叶斯推理是我们直觉的自然延伸。
Psychic ability is simply the natural extension of our intuition.

贝叶斯推理在现实世界中起到了重要作用，是因为它从概率的角度表示预测结果。
Bayesian Inference is useful in the real-world because it expresses predictions in terms of probabilities.

如果大脑的确是按照贝叶斯脑假说的原理活动，那么我们需要进一步了解大脑是如何实现贝叶斯推理的。
If the brain behaves as a Bayesian brain, we need to further our understanding of how the brain actually implements Bayesian Inference.

这种“贝叶斯推理(Bayesianinference)”使得团队在他们的实验中达到的灵敏度比经典相位估计所能达到的灵敏度高出六倍。
This Bayesian inference enabled the team to reach a sensitivity about six times higher than that achieved with classical phase estimation.

频率学派和贝叶斯学派推理方法存在两个主要差异，这些差异未包含在上述概率诠释的考虑中：.
There are two major differences in the frequentist and Bayesian approaches to inference that are not included in the above consideration of the interpretation of probability:.

AdnanDarwiche的ModelingandReasoningwithBayesianNetworks*（CambridgeUniversityPress,2009）一书解释了贝叶斯网络中用于推理的主要算法。
Modeling and Reasoning with Bayesian Networks,* by Adnan Darwiche(Cambridge University Press, 2009), explains the main algorithms for inference in Bayesian networks.