GENERATIVE MODELS in Chinese translation

• 生成模型

Examples of using Generative models in English and their translations into Chinese

However, we're still at the early stages of building generative models that work reasonably well.
但是，我们仍处于构建合理工作的生成模型的初级阶段。

We also demonstrated how to control deep generative models running in the browser to create new music.
我们还演示了，如何控制运行在浏览器中的深度生成模型，制作新的音乐。

Seeking to resolve the confusion and provide historical context,[58] distinguishes between prescribed and implicit generative models.
为了解决该混淆，并提供历史背景，[58]对规定的和隐性的生成模型进行了区分。

Their work, based on the machine-learning approach of generative models, significantly advances the development of self-learning artificial intelligence, while also deepening understanding of human cognition.
他们基于生成模型的机器学习方法的成果显著推动了自我学习人工智能的发展，同时也加深了对人类认知的理解。

Generative Adversarial Networks(GAN)(Goodfellow et al., 2014) are an effective method for training generative models of complex data such as natural images.
生成性对抗网络（GAN）（Goodfellow等，2014）是用于训练复杂数据（如自然图像）的生成模型的有效方法。

They say“Concepts are represented as simple probabilistic programs- that is, probabilistic generative models expressed as structured procedures in an abstract description language.”.
他们说“概念被表征为简单的概率程序--即是说，概率生成模型被表征为抽象描述性语言的结构化步骤。

We could conceivably use any LSTM architecture as a generative model.
我们可以想象地使用任何LSTM体系结构作为生成模型。

Online planners rely on the existence of an accurate generative model.
在线规划模型则依赖于已有的准确的生成模型。

For example, we used a generative model to transfer the motion from one shape to another.
例如，我们使用了一个生成模型将运动从一种形状转移到另一种形状：.

In this, a generative model is much like the human brain: not only can it read digits, it can also write them.
所以，生成式模型更像人类的大脑：不仅可以读数字，还能够写出数字。

ICA defines a generative model for the observed multivariate data, which is typically given as a large database of samples.
ICA对观测到的多变量数据定义了一个生成模型，这通常是作为样本的一个大的数据库。

A generative model will learn categories of data while a discriminative model will simply learn the distinction between different categories of data.
生成模型将学习数据类别，而判别模型将简单地学习不同类别数据之间的区别。

However, if we do need answers to questions like 3- 6, then we have no choice but to use a generative model.
然而，如果我们确实需要像3-6问题的答案，那么我们别无选择，只能使用生成式模型。

This means, for example, that a generative model trained on real images of faces can output new synthetic images of similar faces.
这意味着，例如：在面部的真实图像上训练的生成模型，可以输出相似面部的新合成图像。

Let's think of two models, a generative model and a discriminative model..
假设有两个模型，一个生成模型，一个判别模型。

Let's think of two models, a generative model and a discriminative model..
我们来考虑两个模型，一个生成模型和一个判别模型。

In our data programming approach, we consider the labeling functions as implicitly describing a generative model.
在我们的方法中，我们认为标签函数隐式地描述了一个生成模型。

We also construct continuous normalizing flows, a generative model that can train by maximum likelihood, without partitioning or ordering the data dimensions.
此外，我们还构建了连续的归一化流，即一个可以使用最大似然训练的生成模型，无需对数据维度进行分割或排序。

The answer was quite compelling, here are just a few of possible applications that call for a good generative model.
答案很有说服力，这里给出了几个需要优秀生成模型的可能的应用：.

However, in recent works,“generative model” imprecisely refers to any model that produces realistic-looking structured data.
但是，近期的论文中“generativemodel”不准确地意指生成逼真结构化数据的任意模型。