Document Type
Article
Abstract
Manifolk is a tool to visualize the output of dimensionality reduction algorithms like t-SNE, PCA etc. One of this tool’s main uses is that it de-clutters graphs by plotting data points pertaining to a subset of labels. The subset of labels to be plotted can be selected using the provided checkboxes. A case study on data from a publicly available action recognition dataset like UCF101 shows how this tool can help find outliers. With the rise in self-supervised methods for training deep neural networks, this tool helps researchers better visualize the embeddings learned by the model.
Publication Date
7-2-2021
Language
English
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Recommended Citation
Kodur, Krishna Chaitanya; Ashwin, Ramesh Babu; and Makedon, Fillia, "Manifolk: A 3D t-SNE Visualizer" (2021). Association of Computing Machinery Open Access Agreement Publications. 29.
https://mavmatrix.uta.edu/utalibraries_acmoapubs/29