Hong Ge
- Modeling and Simulation top 0.5%
- Economics and Econometrics top 5%
- Infectious Diseases top 10%
- Molecular Biology
- Clinical Psychology top 10%
- Co-authors
- Julio Sáez-RodríguezMichael P. MendenTimothy RittmanFrancesco IorioYee Whye TehSören MindermannAnna B. StephensonTamay Besiroglu
- Topics
- Bayesian Modeling and Causal Inference (4 papers)Bayesian Methods and Mixture Models (3 papers)Medical Image Segmentation Techniques (2 papers)
- Partner nations
- United KingdomChinaUnited States
In The Last Decade
Hong Ge
22 papers receiving 1.0k citations
Hit Papers
Peers
Comparison fields: 5 of 149
- Modeling and Simulation 452
- Economics and Econometrics 211
- Infectious Diseases 179
- Molecular Biology 179
- Clinical Psychology 133
Countries citing papers authored by Hong Ge
This map shows the geographic impact of Hong Ge'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 Hong Ge with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hong Ge more than expected).
Fields of papers citing papers by Hong Ge
This network shows the impact of papers produced by Hong Ge. 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 Hong Ge. The network helps show where Hong Ge may publish in the future.
Co-authorship network of co-authors of Hong Ge
This figure shows the co-authorship network connecting the top 25 collaborators of Hong Ge. A scholar is included among the top collaborators of Hong Ge 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 Hong Ge. Hong Ge is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 3 | |
| 5 | 9 | |
| 6 | 8 | |
| 7 | 2 | |
| 8 | Inferring the effectiveness of government interventions against COVID-19breakdown → | 630 |
| 9 | 20 | |
| 10 | Bayesian Learning of Sum-Product Networks | 4 |
| 11 | Bijectors.jl: Flexible transformations for probability distributions | 1 |
| 12 | Turing: Composable inference for probabilistic programming. | 5 |
| 13 | 34 | |
| 14 | 65 | |
| 15 | Distributed Inference for Dirichlet Process Mixture Models | 15 |
| 16 | The vegetation cover change in Fen River basin | 1 |
| 17 | 173 | |
| 18 | Three Network DEA Models for Parallel Systems and Selection in Application | 0 |
| 19 | Velocity changes observed by the precisely controlled active source for the Mianzhu M_s 5.6 Earthquake | 6 |
| 20 | 28 |
About Hong Ge
Hong Ge is a scholar working on General Decision Sciences, Statistics and Probability and Artificial Intelligence, having authored 25 papers that have together received 1.1k indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (4 papers), Bayesian Methods and Mixture Models (3 papers) and Medical Image Segmentation Techniques (2 papers). The work is most often cited by research in Modeling and Simulation (452 citations), Infectious Diseases (179 citations) and Health (72 citations). Hong Ge has collaborated with scholars based in United Kingdom, China and United States. Frequent co-authors include Julio Sáez-Rodríguez, Michael P. Menden, Timothy Rittman, Francesco Iorio, Yee Whye Teh, Sören Mindermann, Anna B. Stephenson, Tamay Besiroglu, Leonid Chindelevitch and George Altman. Their work appears in journals such as Science, Nucleic Acids Research and Journal of Hydrology.
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.