arXiv · 2201.03898
An Introduction to Autoencoders
Abstract
In this article, we will look at autoencoders. This article covers the mathematics and the fundamental concepts of autoencoders. We will discuss what they are, what the limitations are, the typical use cases, and we will look at some examples. We will start with a general introduction to autoencoders, and we will discuss the role of the activation function in the output layer and the loss function. We will then discuss what the reconstruction error is. Finally, we will look at typical applications as dimensionality reduction, classification, denoising, and anomaly detection. This paper contains the notes of a PhD-level lecture on autoencoders given in 2021.
Explore related subjects
Keep this discovery
Umberto Michelucci. 2022-01-11. An Introduction to Autoencoders. https://arxiv.org/abs/2201.03898
Cite the original work for its findings. Save a collection to share your selection of sources.