Michael Pearce

516 citations
16 papers · 235 indexed · h-index 8

Impact in

Papers in

Michael Pearce

16 papers receiving 225 citations

Peers

Michael Pearce
Comparison fields: 5 of 68
  • Management Science and Operations Research 55
  • Computational Theory and Mathematics 63
  • Artificial Intelligence 107
  • Statistics, Probability and Uncertainty 19
  • Computer Vision and Pattern Recognition 54
Replace Soroosh Shafieezadeh-Abadeh with:
Soroosh Shafieezadeh-Abadeh Switzerland
Sarah Dean United States
Anastasios N. Angelopoulos United States
Hans-Michael Voigt Germany
Andreas Arning Germany
Jui‐Chung Hung Taiwan
Ray Pörn Finland
Claus Aranha Japan
Ni Ding Australia
Jan Mulawka Poland
Michael Pearce relative to Soroosh Shafieezadeh-Abadeh Switzerland Soroosh Shafieezadeh-Abadeh's profile →
Citations per field
00.5×
Soroosh Shafieezadeh-Abadeh · 1×
Citations per year

Countries citing papers authored by Michael Pearce

Since Specialization
Citations

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

Fields of papers citing papers by Michael Pearce

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 18 scholars most cited alongside Michael Pearce, 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 Michael Pearce Line = papers co-authored together Michael Pearce links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 202210
2 20202
3
The Gaussian Process Prior VAE for Interpretable Latent Dynamics from Pixels
20193
4 201964
5 20194
6 201814
7 20181
8 201810
9 201825
10 20176
11 20171
12 20178
13 20178
14
Efficient information collection on portfolios
20172
15 20052
16 199475

About Michael Pearce

Michael Pearce is a scholar working on Management Science and Operations Research, Computational Theory and Mathematics, Artificial Intelligence, Statistics, Probability and Uncertainty and Software, having authored 16 papers that have together received 235 indexed citations. Recurring topics across this work include Advanced Multi-Objective Optimization Algorithms (7 papers), Gaussian Processes and Bayesian Inference (6 papers), Advanced Bandit Algorithms Research (4 papers), Simulation Techniques and Applications (4 papers), AI-based Problem Solving and Planning (2 papers), Machine Learning and Algorithms (2 papers), Auction Theory and Applications (2 papers) and Advanced Statistical Process Monitoring (2 papers). The work is most often cited by research in Management Science and Operations Research (55 citations), Computational Theory and Mathematics (63 citations), Artificial Intelligence (107 citations), Statistics, Probability and Uncertainty (19 citations) and Computer Vision and Pattern Recognition (54 citations). Michael Pearce has collaborated with scholars based in United Kingdom, United States and Sweden. Frequent co-authors include Juergen Branke, Ashwin Ram, Ronald C. Arkin, Gary Boone, Matthias Poloczek, David Eriksson, R.D. Turner, Jacob R. Gardner, Jason Madan and Simon Day. Their work appears in journals such as ACM Transactions on Modeling and Computer Simulation, Adaptive Behavior, Pharmaceutical Statistics, European Journal of Operational Research and BMC Medical Research Methodology.

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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