What is the translation of " 因果模型 " in English?

• causal models
• causal model

Examples of using 因果模型 in Chinese and their translations into English

我们需要能够发现因果模型的机器。
We need machines that can discover causal models.

我们需要能发现因果模型的机器。
We need machines that can discover causal models.

我们需要能够发现因果模型的机器。
We need machines that can build a causal model.

有关人类婴儿的研究显示，他们是通过搭建因果模型来学习的，而这些模型可以预测他们生活环境的结构。
Studies on human babies show that they learn by building causal models that predict the structure of their living environment.

它还使用因果模型来生成自动提示，例如“Heinz电量不足”或“Heinz电量完全耗尽”。
It also uses causal models to generate automated prompts, such as'Heinz is running low,' or'Heinz has run completely out.'.

珀尔坚称：“我们只有在假设了因果模型之后才收集数据，在我们陈述了我们希望回答的科学问题之后。
We collect data only after we posit the causal model,” Pearl insists,“after we state the scientific query we wish to answer….

因果模型所具备而数据挖掘和深度学习所缺乏的另一个优势就是适应性。
Another advantage causal models have that data mining and deep learning lack is adaptability.

也就是说，适当的被动观测数据可以提供与RCT相同的证据，当然，前提是初始因果模型是准确的。
That is, appropriate passive observational data can provide the same sort of evidence as an RCT- assuming, of course, that the initial causal model is accurate.

结构因果模型（SCM）结合了图形建模、结构方程、反事实和介入逻辑。
Structural Causal Models(SCM) combine graphical modeling, structural equations, and counterfactual and interventional logic.

那并不是真相，但是是合情合理的，而哈利从来没有想过那么具体的因果模型，只是隐约猜到有某种联系。
It wasn't true but it was reasonable and Harry had never thought of any causal model that concrete, just vaguely suspected a connection.

在社会科学领域，尤其是流行病学中，一种名为“结构因果模型”（SCM）的革命性数学框架已经被广泛采用。
In the social sciences and especially epidemiology, a transformative mathematical framework called‘Structural Causal Models'(SCM) has seen widespread adoption.

这本书提供了一个独立的和简明的介绍因果模型和如何学习他们的数据。
This book offers a self-contained and concise introduction to causal models and how to learn them from data.

我们讨论用于不确定情况推理的贝叶斯模型、信念网络、Dempster-Shafer、因果模型以及Stanford确信度代数。
We introduce Bayesian models, belief networks, Dempster-Shafer, causal models, and the Stanford certainty algebra for reasoning in uncertain situations.

这些方法包括传统的生物统计学，贝叶斯数据分析，机器学习和因果模型。
These methods will include traditional biostatistics, Bayesian data analysis, machine learning and causal modelling.

图2：SCM「推断引擎」结合数据和因果模型（或假设），生成查询的答案。
Figure 2: How the SCM“inference engine” combines data with causal model(or assumptions) to produce answers to queries of interest.

还使用了协整和因果模型评估了石油价格对咖啡和可可市场的溢出效应。
Also oil price spillover effects on coffee and cocoa markets were assessed using cointegration and causality models.

要理解“为什么”，并回答“如果……会怎样”之类的问题，我们需要某种因果模型。
To understand why? and to answer what if? questions, we need some kind of a causal model.

然而，这不是微不足道的-交付因果模型推动模拟是非常困难的，需要大量的专业知识，而且只能在有限的容量内完成。
This isn't, however, trivial- delivering causal models to drive simulations is extremely hard, requires significant expertise, and can only be done in a limited capacity.

自20世纪80年代以来，量子科学已经从物理学扩展到神经科学、信息计算、密码学和因果模型，取得了巨大的实际成功。
Since the 1980s, quantum science has expanded beyond physics to neuroscience, information computing, cryptography and causal modelling, with great practical success.

但是，我们如何决定首先测试哪些因果模型呢?
But how do we decide which causal models to test in the first place?

更根本的是，处理组合爆炸需要学习三维世界的因果模型以及它们如何生成图像。
More fundamentally, dealing with the combinatorial explosion requires learning causal models of the 3D world and how these generate images.

对人类婴儿的研究表明，他们通过建立预测所处环境结构的因果模型来学习。
Studies on human babies show that they learn by building causal models that predict the structure of their living environment.

在下面这张动图中，图式网络通过使用其关于世界的因果模型，演示了如何对很多潜在的未来进行推理：.
Below is a visualization showing how the Schema Network reasons about many potential futures by using its causal model of the world:.

为了防止该模型因果循环，需要时间元素。
In order to prevent this model from being causally circular, a time element is required.

因为我们永远不会得到一个完美的现实因果推理模型；.
We don't have a perfect causal model of the reality;

因果联系模型试图分析数据，并观察两组变量之间是否存在因果关系。
Causal models try to consume data and see if there's a causal relationship between two sets of variables and so on.

建立理解，规划和积极因果学习的世界模型.
Building world models for understanding, planning, and active causal learning.

各类常用因果模型，都可以看作SCM的子类。
All of the other models can be considered special cases of FIGGM.

机器现在还不行，因为它们没有因果推理模型。
Machines are not, because they don't have these causal models.