Diederik P. Kingma

About

Diederik P. Kingma is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Statistical and Nonlinear Physics. According to data from OpenAlex, Diederik P. Kingma has authored 19 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computer Vision and Pattern Recognition, 10 papers in Artificial Intelligence and 7 papers in Statistical and Nonlinear Physics. Recurrent topics in Diederik P. Kingma’s work include Generative Adversarial Networks and Image Synthesis (11 papers), Model Reduction and Neural Networks (7 papers) and Gaussian Processes and Bayesian Inference (5 papers). Diederik P. Kingma is often cited by papers focused on Generative Adversarial Networks and Image Synthesis (11 papers), Model Reduction and Neural Networks (7 papers) and Gaussian Processes and Bayesian Inference (5 papers). Diederik P. Kingma collaborates with scholars based in United States, The Netherlands and United Kingdom. Diederik P. Kingma's co-authors include Max Welling, Tim Salimans, Shakir Mohamed, Danilo Jimenez Rezende, Prafulla Dhariwal, Ilya Sutskever, Ruiqi Gao, Xi Chen, Yan Duan and John Schulman and has published in prestigious journals such as 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), arXiv (Cornell University) and Neural Information Processing Systems.

In The Last Decade

Co-authorship network of co-authors of Diederik P. Kingma i

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Fields of papers citing papers by Diederik P. Kingma

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Diederik P. Kingma. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Diederik P. Kingma. The network helps show where Diederik P. Kingma may publish in the future.

Countries citing papers authored by Diederik P. Kingma

Since Specialization

Citations

This map shows the geographic impact of Diederik P. Kingma's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Diederik P. Kingma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Diederik P. Kingma more than expected).

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar’s output or impact.

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