The DOI matches its Crossref record; 298 of the 306 references it cites were found in a registry or an index.
Visualizing High-Dimensional Data: Advances in the Past Decade
Abstract
Massive simulations and arrays of sensing devices, in combination with increasing computing resources, have generated large, complex, high-dimensional datasets used to study phenomena across numerous fields of study. Visualization plays an important role in exploring such datasets. We provide a comprehensive survey of advances in high-dimensional data visualization that focuses on the past decade. We aim at providing guidance for data practitioners to navigate through a modular view of the recent advances, inspiring the creation of new visualizations along the enriched visualization pipeline, and identifying future opportunities for visualization research.
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“On the contrary, some papers related to the Software Design KA were not related to the Software Construction KA [12,13,19,20].”
From Software engineering challenges for machine learning applications: A literature review (2020) · cites this paper as [13]
In the citing paper
“Several software processes for ML applications have been proposed [13,19,30,67,88,89].”
From Software engineering challenges for machine learning applications: A literature review (2020) · cites this paper as [13]
Citations
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Cited by
Sorted by citations
Visual Analytics in Deep Learning: An Interrogative Survey for the Next Frontiers
Hohman, F., Kahng, M., Pienta, R., & Chau, D. H. (2019) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2018.2843369 · Cited by 582
Zio, E. (2018) · Reliability Engineering & System Safety · doi:10.1016/j.ress.2018.04.020 · Cited by 456
CNN Explainer: Learning Convolutional Neural Networks with Interactive Visualization
Wang, Z. J., Turko, R., Shaikh, O., Park, H., Das, N., Hohman, F., Kahng, M., & Chau, D. H. (2020) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2020.3030418 · Cited by 362
Generative Adversarial Networks for face generation: A survey
Kammoun, A., Slama, R., Tabia, H., Ouni, T., & Abid, M. (2022) · ACM Computing Surveys · doi:10.1145/1122445.1122456 · Cited by 370
Toward a Quantitative Survey of Dimension Reduction Techniques
Espadoto, M., Martins, R. M., Kerren, A., Hirata, N. S. T., & Telea, A. C. (2019) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2019.2944182 · Cited by 348
Metadata
- Authors
- Liu, S., Maljovec, D., Wang, B., Bremer, P.-T., & Pascucci, V.
- Affiliations
- University of Utah (US)
- Lawrence Livermore National Laboratory (US)
- Venue
- IEEE Transactions on Visualization and Computer Graphics
- Published
- 2017-03-01
- Volume
- 23
- Issue
- 3
- Pages
- 1249-1268
- ISSN
- 1077-2626 (ISSN-L)
- OpenAlex
- W2323909273
- Cited by
- 427
- References
- 306
- Citations by year
- 2026: 25 · 2025: 34 · 2024: 45 · 2023: 46 · 2022: 45 · 2021: 52 · 2020: 62 · 2019: 49 · 2018: 32 · 2017: 21
- FWCI
- 26.07
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Transactions on Visualization and Computer Graphics (publishedVersion)
- PubMed (publishedVersion)
- Funders
- US DOE
- LLNL (DE-AC52-07NA27344, LLNL-CONF-658933)
- US National Science Foundation (IIS-1513616, 0904631, DE-EE0004449, DE-NA0002375, DE-SC0007446, DE-SC0010498, NSG IIS-1045032, NSF EFT ACI-0906379, DOE/NEUP 120341, DOE/Codesign P01180734)
- Topics
- Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › Data Visualization and Analytics
- Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › Computer Graphics and Visualization Techniques
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Topological and Geometric Data Analysis
- Keywords
- high-dimensional data visualization, dimensionality reduction, visualization pipeline, large-scale datasets
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