Papers
arxiv:2104.02726

Creativity and Machine Learning: A Survey

Published on Apr 6, 2021
Authors:
,

Abstract

The survey reviews the history and current state of computational creativity theories, focusing on generative deep learning and evaluation methods, and discusses research challenges and opportunities.

AI-generated summary

There is a growing interest in the area of machine learning and creativity. This survey presents an overview of the history and the state of the art of computational creativity theories, key machine learning techniques (including generative deep learning), and corresponding automatic evaluation methods. After presenting a critical discussion of the key contributions in this area, we outline the current research challenges and emerging opportunities in this field.

Community

Sign up or log in to comment

Models citing this paper 0

No model linking this paper

Cite arxiv.org/abs/2104.02726 in a model README.md to link it from this page.

Datasets citing this paper 0

No dataset linking this paper

Cite arxiv.org/abs/2104.02726 in a dataset README.md to link it from this page.

Spaces citing this paper 1

Collections including this paper 0

No Collection including this paper

Add this paper to a collection to link it from this page.