Heiko Strathmann
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 10%
- Statistics and Probability top 5%
- Control and Systems Engineering top 10%
- Mechanical Engineering
- Co-authors
- Arthur GrettonDino SejdinovićSivaraman BalakrishnanMassimiliano PontilBharath K. SriperumbudurKenji FukumizuChristophe AndrieuAnne-Marie Lyne
- Topics
- Markov Chains and Monte Carlo Methods (5 papers)Gaussian Processes and Bayesian Inference (3 papers)Statistical Methods and Bayesian Inference (2 papers)
- Partner nations
- United KingdomUnited StatesAustralia
In The Last Decade
Heiko Strathmann
13 papers receiving 519 citations
Hit Papers
Peers
Comparison fields: 5 of 98
- Artificial Intelligence 276
- Computer Vision and Pattern Recognition 125
- Statistics and Probability 104
- Control and Systems Engineering 78
- Mechanical Engineering 45
Countries citing papers authored by Heiko Strathmann
This map shows the geographic impact of Heiko Strathmann'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 Heiko Strathmann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Heiko Strathmann more than expected).
Fields of papers citing papers by Heiko Strathmann
This network shows the impact of papers produced by Heiko Strathmann. 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 Heiko Strathmann. The network helps show where Heiko Strathmann may publish in the future.
Co-authorship network of co-authors of Heiko Strathmann
This figure shows the co-authorship network connecting the top 25 collaborators of Heiko Strathmann. A scholar is included among the top collaborators of Heiko Strathmann 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 Heiko Strathmann. Heiko Strathmann is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | NeRF-VAE: A Geometry Aware 3D Scene Generative Model | 19 |
| 2 | Persistent Message Passing | 1 |
| 3 | 3 | |
| 4 | Deep Self-Organization: Interpretable Discrete Representation Learning on Time Series | 6 |
| 5 | Efficient and principled score estimation. | 1 |
| 6 | 23 | |
| 7 | 14 | |
| 8 | 43 | |
| 9 | 31st International Conference on Machine Learning, ICML 2014 | 74 |
| 10 | Playing Russian Roulette with Intractable Likelihoods | 9 |
| 11 | 9 | |
| 12 | Optimal kernel choice for large-scale two-sample testsbreakdown → | 312 |
| 13 | 19 |
About Heiko Strathmann
Heiko Strathmann is a scholar working on Statistics and Probability, Computer Graphics and Computer-Aided Design and Virology, having authored 13 papers that have together received 533 indexed citations. Recurring topics across this work include Markov Chains and Monte Carlo Methods (5 papers), Gaussian Processes and Bayesian Inference (3 papers) and Statistical Methods and Bayesian Inference (2 papers). The work is most often cited by research in Statistics and Probability (104 citations), Artificial Intelligence (276 citations) and Computer Vision and Pattern Recognition (125 citations). Heiko Strathmann has collaborated with scholars based in United Kingdom, United States and Australia. Frequent co-authors include Arthur Gretton, Dino Sejdinović, Sivaraman Balakrishnan, Massimiliano Pontil, Bharath K. Sriperumbudur, Kenji Fukumizu, Christophe Andrieu, Anne-Marie Lyne, Yves F. Atchadé and Mark Girolami. Their work appears in journals such as Journal of Virology, IEEE Access and Statistical Science.
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.