Mark Girolami
Impact in
- Signal Processing top 0.2%
- Blind Source Separation Techniques
- Statistics and Probability top 0.2%
- Markov Chains and Monte Carlo Methods
Papers in
-
- Gaussian Processes and Bayesian Inference 39
- Neural Networks and Applications 22
- Bayesian Methods and Mixture Models 16
- Co-authors
- Terrence J. Sejnowski (3 shared papers)Ben Calderhead (11 shared papers)Te-Won Lee (1 shared paper)Simon Rogers (14 shared papers)Ata Kabán (11 shared papers)Theodoros Damoulas (9 shared papers)Ioannis Brilakis (3 shared papers)Rafael Sacks (2 shared papers)
- Journals
- Bioinformatics (10 papers)Journal of Computational Physics (9 papers)Neural Computation (8 papers)Pattern Recognition Letters (7 papers)Computer Methods in Applied Mechanics and Engineering (4 papers)
- Partner nations
- United KingdomUnited StatesGermany
In The Last Decade
Mark Girolami
230 papers receiving 9.8k citations
Mark Girolami's Hit Papers
Peers
Comparison fields: 5 of 215
- Signal Processing 1.9k
- Statistics and Probability 1.0k
- Artificial Intelligence 3.3k
- Cognitive Neuroscience 1.4k
- Statistics, Probability and Uncertainty 520
Countries citing papers authored by Mark Girolami
This map shows the geographic impact of Mark Girolami'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 Mark Girolami with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark Girolami more than expected).
Fields of papers citing papers by Mark Girolami
This network shows the impact of papers produced by Mark Girolami. 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 Mark Girolami. The network helps show where Mark Girolami may publish in the future.
Co-authors
The 25 scholars most cited alongside Mark Girolami, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 236 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Independent Component Analysis Using an Extended Infomax Algorithm for Mixed Subgaussian and Supergaussian Sources Hit paper breakdown → | 1999 | 1364 |
| 2 | Riemann Manifold Langevin and Hamiltonian Monte Carlo Methods Hit paper breakdown → | 2011 | 777 |
| 3 | Mercer kernel-based clustering in feature space Hit paper breakdown → | 2002 | 588 |
| 4 | Machine learning and structural health monitoring overview with emerging technology and high-dimensional data source highlights Hit paper breakdown → | 2021 | 344 |
| 5 | Construction with digital twin information systems Hit paper breakdown → | 2020 | 326 |
| 6 | 1999 | 260 | |
| 7 | The geometric foundations of Hamiltonian Monte Carlo Hit paper breakdown → | 2017 | 220 |
| 8 | 2007 | 219 | |
| 9 | 2000 | 217 | |
| 10 | 2020 | 168 | |
| 11 | 2001 | 155 | |
| 12 | 2003 | 147 | |
| 13 | 2018 | 140 | |
| 14 | 2021 | 131 | |
| 15 | 2007 | 130 | |
| 16 | 2006 | 124 | |
| 17 | 2003 | 120 | |
| 18 | 2016 | 117 | |
| 19 | 2000 | 116 | |
| 20 | 2008 | 113 |
About Mark Girolami
Mark Girolami is a scholar working on Artificial Intelligence, Molecular Biology, Signal Processing, Statistics and Probability and Statistics, Probability and Uncertainty, having authored 236 papers that have together received 10.4k indexed citations. Recurring topics across this work include Gaussian Processes and Bayesian Inference (39 papers), Blind Source Separation Techniques (29 papers), Probabilistic and Robust Engineering Design (25 papers), Markov Chains and Monte Carlo Methods (23 papers), Neural Networks and Applications (22 papers), Bayesian Methods and Mixture Models (16 papers), Model Reduction and Neural Networks (14 papers) and Structural Health Monitoring Techniques (14 papers). The work is most often cited by research in Signal Processing (1.9k citations), Statistics and Probability (1.0k citations), Artificial Intelligence (3.3k citations), Cognitive Neuroscience (1.4k citations) and Statistics, Probability and Uncertainty (520 citations). Mark Girolami has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Terrence J. Sejnowski, Ben Calderhead, Te-Won Lee, Simon Rogers, Ata Kabán, Theodoros Damoulas, Ioannis Brilakis, Rafael Sacks, Vladislav Vyshemirsky and Chao He. Their work appears in journals such as Bioinformatics, Journal of Computational Physics, Neural Computation, Pattern Recognition Letters and Computer Methods in Applied Mechanics and Engineering.
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.