# Multimapper: Data Density Sensitive Topological Visualization

@article{Deb2018MultimapperDD, title={Multimapper: Data Density Sensitive Topological Visualization}, author={Bishal Deb and Ankita Sarkar and Nupur Kumari and Akash Rupela and Piyush Kumar Gupta and Balaji Krishnamurthy}, journal={2018 IEEE International Conference on Data Mining Workshops (ICDMW)}, year={2018}, pages={1054-1061} }

Mapper is an algorithm that summarizes the topological information contained in a dataset and provides an insightful visualization. It takes as input a point cloud which is possibly high-dimensional, a filter function on it and an open cover on the range of the function. It returns the nerve simplicial complex of the pullback of the cover. Mapper can be considered a discrete approximation of the topological construct called Reeb space, as analysed in the 1-dimensional case by [Carri et al…

## One Citation

### ShapeVis: High-dimensional Data Visualization at Scale

- Computer ScienceWWW
- 2020

ShapeVis is presented, a scalable visualization technique for point cloud data inspired from topological data analysis that captures the underlying geometric and topological structure of the data in a compressed graphical representation and demonstrates how it captures the structural characteristics of real and synthetic data sets.

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