We will look into the various approaches of generative models in the following sections.
Generative models
Autoregressive models
Autoregressive models estimate the conditional distribution of some data , given some other values of y. For example, in image synthesis, it estimates the conditional distribution of pixels given surrounding or previous pixels; in audio synthesis, it estimates the conditional distribution of audio samples given previous audio samples and spectrograms.
In its simplest linear form, with dependency on the previous time-step only and time-invariant bias term, an autoregressive model can be defined with the following equation:
![](https://static.packt-cdn.com/products/9781789538205/graphics/assets/e9b27f32-e7d0-436d-b1a5-7b5ae19f733c.png)
is a constant term that represents the model's bias,
represents the...