Samuli Laine: h-index, Total Citations, and Citation Map
Samuli Laine's h-index is 20 (20 i10-index, 69,657+ total citations across 20+ publications) according to Google Scholar as of July 2026. Samuli Laine is affiliated with Distinguished Research Scientist, NVIDIA.
Samuli Laine is a researcher affiliated with Distinguished Research Scientist, NVIDIA, specializing in various fields. Their work has been cited 69,657 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Samuli Laine's Citation Metrics
Bibliometric impact based on 20 indexed publications.
- H-Index
- 20
- i10-Index
- 20
- Total Citations
- 69,657
- Citing Countries
- 48
As of July 2026.
Samuli Laine has an h-index of 20 and 69,657 total citations across 20 publications, with research cited by institutions in 48 countries.
Download Exports (PNG, CSV, Poster)
Free Viewing Samuli Laine's citation map is always free. Pay once to download poster, PNG, and CSV files for offline use or your visa packet.
Global Impact Map
Visualizing the geographic distribution of institutions that have cited your work.
Starting…
Pins will appear here as institutions are resolved — no need to refresh.
Progressive Growing of GANs for Improved Quality, Stability, and\n Variation
20172,871
Top Citing Countries
Top Citing Institutions
Visa Evidence Package
Views and exports tuned for EB-1A, O-1A, and EB-2 NIW petitions. Sustained acclaim, geographic reach, and independent-citation filtering are the strongest evidence categories immigration adjudicators look for.
Significant Contributions
Auto-detected research lines — a seminal paper and the follow-up work building on it. Review and edit before using in a petition. Each Free PDF opens in a new tab — EB-1A organises this into the structure USCIS applies to Criterion 5 of 8 CFR § 204.5(h)(3)(v); EB-1B re-frames it under § 204.5(i)(3) (outstanding researcher); NIW presents it under prong 2 of Matter of Dhanasar.
13 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher advanced GPU ray traversal efficiency through seminal work on sparse voxel octrees, establishing a foundational framework widely adopted by independent researchers in computer graphics.
The researcher developed a progressive growing method for GANs that significantly improved generation quality, training stability, and output variation.
The researcher introduced temporal ensembling for semi-supervised learning, a seminal approach that has garnered over 1,400 citations and established a foundational method in the field.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
Related Guides
Learn how to use citation maps for your research and visa applications.
About Samuli Laine's research
Samuli Laine is a researcher at Distinguished Research Scientist, NVIDIA. Their work has been cited 69,657 times across 20 publications (h-index 20), according to Google Scholar.
Their most-cited work, “Progressive Growing of GANs for Improved Quality, Stability, and\n Variation” (2017), has accumulated 2,871 citations. Other influential works include “Temporal Ensembling for Semi-Supervised Learning” (2016) with 1,496 citations and “Noise2Noise: Learning Image Restoration without Clean Data” (2018) with 982 citations.
Citations of Samuli Laine's research come primarily from China, United States and Germany, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.











