Work

G-Rap: interactive text synthesis using recurrent neural network suggestions

Year: 2018

Type: conference-paper

Abstract: Finding the best neural network configuration for a given goal can be challenging, especially when it is not possible to assess the output quality of a network automatically. We present G-Rap, an interactive interface based on Visual Analytics principles for comparing outputs of multiple RNNs for the same training data. G-Rap enables an iterative result generation process that allows a user to evaluate the outputs with contextual statistics.

Source: KOPS (University of Konstanz)

Authors: Udo Schlegel, Eren Cakmak, Juri Buchmüller, Daniel A. Keim

Institution: University of Konstanz

Language: English

Topic: Data Visualization and Analytics

Subfield: Computer Graphics and Computer-Aided Design

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W2801280546

FWCI: 0.124

Cites: 20

Cited by: 1

Related to: 10