What are generative models?

A generative model includes the distribution of the data itself, and tells you how likely a given example is. For example, models that predict the next word in a sequence are typically generative models (usually much simpler than GANs) because they can assign a probability to a sequence of words.

Which of the following is an example of generative models?

An example of a generative model might be one that is trained on collections of images from the real world in order to generate similar images. The model might take observations from a 200GB set of images and reduce them into 100MB of weights. Weights can be thought of as reinforced neural connections.

Is CNN generative model?

The convolutional neural networks (CNNs) have proven to be a powerful tool for discriminative learning. The main contributions include: (1) We construct a generative model for the CNN in the form of exponential tilting of a reference distribution.

Is GMM a generative model?

The fact that GMM is a generative model gives us a natural means of determining the optimal number of components for a given dataset.

Is PCA a generative model?

Dimensionality reduction methods can be categorized into two groups: generative (typically unsupervised) and discriminative (typically supervised) methods. One of the most well-known unsupervised dimensionality reduction methods is Principal Component Analysis (PCA).

Is SVM generative?

Generative models such as HMMs and GMMs focus on estimating the density of the data and are not suitable for classifying the data of confusable classes. Discriminative classifiers such as support vector machines (SVM) are suitable for the fixed dimensional patterns.

Is PCA discriminative?

The most innovation of Discriminative PCA is performing PCA on discriminative matrix rather than original sample matrix. Not only the superiority and outstanding performance of Discriminative PCA showed in recognition rate, but also the comparable results of running time.