Roman Garnett

5.7k citations
71 papers · 1.8k indexed · 2 hit papers · h-index 19

Roman Garnett

70 papers receiving 1.7k citations

Hit Papers

Bayesian O...2632005202620122019100200300400

Peers

Roman Garnett
Comparison fields: 5 of 155
  • Media Technology 269
  • Computer Vision and Pattern Recognition 548
  • Artificial Intelligence 535
  • Computational Theory and Mathematics 203
  • Signal Processing 129
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Citations per field
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Citations per year

Countries citing papers authored by Roman Garnett

Since Specialization
Citations

This map shows the geographic impact of Roman Garnett'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 Roman Garnett with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Roman Garnett more than expected).

Fields of papers citing papers by Roman Garnett

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Roman Garnett. 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 Roman Garnett. The network helps show where Roman Garnett may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Roman Garnett, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Roman Garnett Line = papers co-authored together Roman Garnett links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20251
2 20251
3 20243
4 20235
5 20238
6 20225
7
Cost Effective Active Search
20192
8
Automating Bayesian optimization with Bayesian optimization
20188
9
Efficient Nonmyopic Active Search
20179
10 20173
11
Discovering and Exploiting Additive Structure for Bayesian Optimization
201729
12
BASC: applying Bayesian optimization to the search for global minima on potential energy surfaces
201615
13 201636
14
Bayesian optimization for automated model selection
201627
15
Active Pointillistic Pattern Search
20152
16
Active Area Search via Bayesian Quadrature
20145
17
Σ-Optimality for Active Learning on Gaussian Random Fields
201316
18
Coinciding Walk Kernels: Parallel Absorbing Random Walks for Learning with Graphs and Few Labels
20134
19
Bayesian Quadrature for Ratios
20128
20
Active Learning of Model Evidence Using Bayesian Quadrature
201224

About Roman Garnett

Roman Garnett is a scholar working on Artificial Intelligence, Management Science and Operations Research and Instrumentation, having authored 71 papers that have together received 1.8k indexed citations. Recurring topics across this work include Gaussian Processes and Bayesian Inference (19 papers), Machine Learning and Algorithms (14 papers), Advanced Bandit Algorithms Research (10 papers), Optimization and Search Problems (7 papers), Control Systems and Identification (7 papers), Fault Detection and Control Systems (5 papers), Data Visualization and Analytics (5 papers) and Gamma-ray bursts and supernovae (5 papers). The work is most often cited by research in Media Technology (269 citations), Computer Vision and Pattern Recognition (548 citations) and Artificial Intelligence (535 citations). Roman Garnett has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Charles K. Chui, Wenjie He, Stephen Roberts, Michael A. Osborne, Kristian Kersting, Marion Neumann, Simeon Bird, Christian Bauckhage, Samuel B. Powell and N. Justin Marshall. Their work appears in journals such as Journal of Biological Chemistry, The Journal of Chemical Physics and SHILAP Revista de lepidopterología.

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.

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