Pete Bunch

409 citations
14 papers · 242 · h-index 10

Impact in

    • Target Tracking and Data Fusion in Sensor Networks
    • Gaussian Processes and Bayesian Inference
    • Geology and Paleoclimatology Research
    • Cryospheric studies and observations
    • Arctic and Antarctic ice dynamics

Papers in

Pete Bunch

13 papers receiving 238 citations

Peers

Pete Bunch
Comparison fields: 5 of 43
  • Artificial Intelligence 145
  • Atmospheric Science 78
  • Statistics and Probability 20
  • Oceanography 22
  • Control and Systems Engineering 41
Replace Qiuze Yu with:
Qiuze Yu China
Antonio Natale Italy
H. R. Wason India
Julie Bessac United States
Y.C. Tzeng Taiwan
Taylor Glenn United States
Mauro Palo Italy
Léonard Seydoux France
Tieding Lu China
Richard J. Weiland United Kingdom
Pete Bunch relative to Qiuze Yu China Qiuze Yu's profile →
Citations per field
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Qiuze Yu · 1×
Citations per year

Countries citing papers authored by Pete Bunch

Since Specialization
Citations

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

Fields of papers citing papers by Pete Bunch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 15 scholars most cited alongside Pete Bunch, 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 Pete Bunch Line = papers co-authored together Pete Bunch links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 201652
2 201545
3 201725
4 201523
5 201221
6 201318
7 201216
8 201311
9
Dynamical models for tracking with the variable rate particle filter
20129
10 20169
11
Sparse structure inference for group and network tracking
20166
12 20136
13 20111
14 20150

About Pete Bunch

Pete Bunch is a scholar working on Artificial Intelligence, Control and Systems Engineering, Oceanography, Computer Networks and Communications and Computer Vision and Pattern Recognition, having authored 14 papers that have together received 242 indexed citations. Recurring topics across this work include Target Tracking and Data Fusion in Sensor Networks (10 papers), Gaussian Processes and Bayesian Inference (5 papers), Fault Detection and Control Systems (4 papers), Bayesian Methods and Mixture Models (4 papers), Underwater Acoustics Research (3 papers), Distributed Sensor Networks and Detection Algorithms (2 papers), Geology and Paleoclimatology Research (2 papers) and Cryospheric studies and observations (2 papers). The work is most often cited by research in Artificial Intelligence (145 citations), Atmospheric Science (78 citations), Statistics and Probability (20 citations), Oceanography (22 citations) and Control and Systems Engineering (41 citations). Pete Bunch has collaborated with scholars based in United Kingdom, Sweden and Finland. Frequent co-authors include Simon Godsill, Paul J. Valdes, Max Holloway, Louise C. Sime, Simo Särkkä, Joy Singarayer, Thomas B. Schön, Julia C. Tindall, Fredrik Lindsten and Jamie Murphy. Their work appears in journals such as IEEE Transactions on Signal Processing, IEEE Journal of Selected Topics in Signal Processing, Nature Communications, Journal of the American Statistical Association and Geophysical Research Letters.

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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