Richard Rohwer
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 10%
- Cognitive Neuroscience
- Statistical and Nonlinear Physics top 10%
- Control and Systems Engineering
- Co-authors
- Huaiyu ZhuSteve RenalsDayne FreitagChristopher K. I. WilliamsJohn ByrnesM. BlumeZhiqiang WangEdmond Chow
- Topics
- Neural Networks and Applications (18 papers)Advanced Statistical Methods and Models (4 papers)Speech and Audio Processing (3 papers)
- Partner nations
- United KingdomUnited States
In The Last Decade
Richard Rohwer
28 papers receiving 397 citations
Peers
Comparison fields: 5 of 116
- Artificial Intelligence 264
- Computer Vision and Pattern Recognition 67
- Cognitive Neuroscience 48
- Statistical and Nonlinear Physics 46
- Control and Systems Engineering 38
Countries citing papers authored by Richard Rohwer
This map shows the geographic impact of Richard Rohwer'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 Richard Rohwer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Richard Rohwer more than expected).
Fields of papers citing papers by Richard Rohwer
This network shows the impact of papers produced by Richard Rohwer. 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 Richard Rohwer. The network helps show where Richard Rohwer may publish in the future.
Co-authorship network of co-authors of Richard Rohwer
This figure shows the co-authorship network connecting the top 25 collaborators of Richard Rohwer. A scholar is included among the top collaborators of Richard Rohwer 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 Richard Rohwer. Richard Rohwer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 39 | |
| 5 | 8 | |
| 6 | 17 | |
| 7 | 3 | |
| 8 | Gaussian regression and optimal finite dimensional linear models | 47 |
| 9 | 28 | |
| 10 | 2 | |
| 11 | 17 | |
| 12 | Bayesian invariant measurements of generalisation for discrete distributions | 1 |
| 13 | 6 | |
| 14 | 23 | |
| 15 | A Bayesian formulation of search, control and the exploration/exploitation trade-off | 1 |
| 16 | A representation of representation applied to a discussion of variable binding | 0 |
| 17 | 2 | |
| 18 | 0 | |
| 19 | Time Trials on Second-Order and Variable-Learning-Rate Algorithms | 1 |
| 20 | Neural networks for speech pattern classification | 1 |
About Richard Rohwer
Richard Rohwer is a scholar working on Artificial Intelligence, Statistics and Probability and Signal Processing, having authored 31 papers that have together received 439 indexed citations. Recurring topics across this work include Neural Networks and Applications (18 papers), Advanced Statistical Methods and Models (4 papers) and Speech and Audio Processing (3 papers). The work is most often cited by research in Artificial Intelligence (264 citations), Statistical and Nonlinear Physics (46 citations) and Statistics and Probability (30 citations). Richard Rohwer has collaborated with scholars based in United Kingdom and United States. Frequent co-authors include Huaiyu Zhu, Steve Renals, Dayne Freitag, Christopher K. I. Williams, John Byrnes, M. Blume, Zhiqiang Wang, Edmond Chow, Roger Tarling and Joseph Harrington. Their work appears in journals such as Behavioral and Brain Sciences, Neural Computation and Neural Networks.
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.