NSF 1815238 -- III: Small: An end-to-end pipeline for interactive visual analysis of big data
Summary
This is the webpage for the NSF project “III: Small: An end-to-end pipeline for interactive visual analysis of big data”.
-
Duration: September 1st, 2018 – August 31st, 2021.
-
NSF Information: award page, NSF-1815238.
-
Original proposal document: pdf.
Personnel
-
PhD Student: Zhe Wang (now graduated)
-
PhD Student: Mingwei Li (5th year)
-
PhD Student: Zhenge Zhao (5th year)
Publications
-
NeuralCubes: Deep Representations for Visual Data Exploration. Zhe Wang, Dylan Cashman, Mingwei Li, Jixian Li, Matthew Berger, Joshua A. Levine, Remco Chang, Carlos Scheidegger. arXiv preprint arXiv:1808.08983.
-
Disentangling Influence: Using disentangled representations to audit model predictions. Charles Marx, Richard Phillips, Sorelle Friedler, Carlos Scheidegger, Suresh Venkatasubramanian. Proceedings of NeurIPS 2019.
-
A Structured Review of Data Management Technology for Interactive Visualization and Analysis. Leilani Battle and Carlos Scheidegger, IEEE VIS 2020.
-
Visualizing Neural Networks with the Grand Tour. Mingwei Li, Zhenge Zhao, Carlos Scheidegger. Distill. DOI: 10.23915/distill.00025
-
Anteater: Interactive Visualization for Program Understanding. Rebecca Faust, Kate Isaacs, William Bernstein, Michael Sharp, Carlos Scheidegger. arXiv preprint arXiv:1907.02872.
Software
-
pothos is the code platform for the data cube research in this project.
-
neuralcubes is the code platform for the deep neural networks used to approximate data cubes in NeuralCubes.
Acknowledgments
This material is based upon work supported or partially supported by the National Science Foundation under Grant Number 1815238, project titled “III: Small: An end-to-end pipeline for interactive visual analysis of big data”
Any opinions, findings, and conclusions or recommendations expressed in this project are those of author(s) and do not necessarily reflect the views of the National Science Foundation.
Web page last update: 2020-02-13.