Diederik P. Kingma Google Scholar: h-index, Total Citations, and Citation Map
Diederik P. Kingma's h-index is 62 (81 i10-index, 389,711+ total citations across 94+ publications) according to Google Scholar as of November 2026. Diederik P. Kingma is affiliated with Anthropic.
Diederik P. Kingma is a researcher affiliated with Anthropic, specializing in AI & Machine Learning. Their work has been cited 389,711 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Diederik P. Kingma's Citation Metrics
Bibliometric impact based on 94 indexed publications.
- H-Index
- 62
- i10-Index
- 81
- Total Citations
- 389,711
- Citing Countries
- 46
As of November 2026.
Diederik P. Kingma has an h-index of 62 and 389,711 total citations across 94 publications, with research cited by institutions in 46 countries.
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Adam: A Method for Stochastic Optimization
2014250,341
Top Citing Countries
Top Citing Institutions
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Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Diederik P. Kingma's research
Diederik P. Kingma is a researcher in AI & Machine Learning at Anthropic. Their work has been cited 389,711 times across 94 publications (h-index 62), according to Google Scholar.
Their most-cited work, “Adam: A Method for Stochastic Optimization” (2014), has accumulated 250,341 citations. Other influential works include “Auto-Encoding Variational Bayes” (2013) with 61,314 citations and “Score-based generative modeling through stochastic differential equations” (2020) with 14,941 citations.
Citations of Diederik P. Kingma's research come primarily from United States, China and United Kingdom, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
