This map shows the geographic impact of Nhat Ho'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 Nhat Ho with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nhat Ho more than expected).
This network shows the impact of papers produced by Nhat Ho. 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 Nhat Ho. The network helps show where Nhat Ho may publish in the future.
Co-authorship network of co-authors of Nhat Ho
This figure shows the co-authorship network connecting the top 25 collaborators of Nhat Ho.
A scholar is included among the top collaborators of Nhat Ho based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Nhat Ho. Nhat Ho is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Le, Trung, et al.. (2021). LAMDA: Label Matching Deep Domain Adaptation. Monash University Research Portal (Monash University). 6043–6054.7 indexed citations
10.
Lin, Tianyi, Nhat Ho, Xi Chen, Marco Cuturi, & Michael I. Jordan. (2020). Fixed-Support Wasserstein Barycenters: Computational Hardness and Fast Algorithm. Neural Information Processing Systems. 33. 5368–5380.2 indexed citations
11.
Ho, Nhat, et al.. (2020). Fast Algorithms for Computational Optimal Transport and Wasserstein Barycenter.. International Conference on Artificial Intelligence and Statistics. 2088–2097.1 indexed citations
Ho, Nhat, et al.. (2019). Probabilistic Multilevel Clustering via Composite Transportation Distance. Monash University Research Portal (Monash University). 3149–3157.3 indexed citations
14.
Lin, Tianyi, Nhat Ho, & Michael I. Jordan. (2019). On Efficient Optimal Transport: An Analysis of Greedy and Accelerated Mirror Descent Algorithms. International Conference on Machine Learning. 3982–3991.6 indexed citations
15.
Le, Tam, Nhat Ho, & Makoto Yamada. (2019). Fast Tree Variants of Gromov-Wasserstein. arXiv (Cornell University).1 indexed citations
16.
Ho, Nhat, et al.. (2019). Accelerated Primal-Dual Coordinate Descent for Computational Optimal Transport.. arXiv (Cornell University).1 indexed citations
17.
Lin, Tianyi, Nhat Ho, & Michael I. Jordan. (2019). On the Acceleration of the Sinkhorn and Greenkhorn Algorithms for Optimal Transport. arXiv (Cornell University).2 indexed citations
18.
Ho, Nhat, et al.. (2018). Theoretical guarantees for EM under misspecified Gaussian mixture models. Neural Information Processing Systems. 31. 9681–9689.3 indexed citations
19.
Ho, Nhat. (2017). Parameter Estimation and Multilevel Clustering with Mixture and Hierarchical Models. Deep Blue (University of Michigan).2 indexed citations
20.
Ho, Nhat, et al.. (2017). Multilevel Clustering via Wasserstein Means. Own your potential (DEAKIN). 1501–1509.8 indexed citations
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.