Tom Downs

918 citations
48 papers · 685 · h-index 13

Impact in

    • Neural Networks and Applications
    • Metaheuristic Optimization Algorithms Research
    • Evolutionary Algorithms and Applications
    • Machine Learning and ELM
  • Software top 10%

Papers in

Tom Downs

41 papers receiving 629 citations

Peers

Tom Downs
Comparison fields: 5 of 83
  • Artificial Intelligence 412
  • Software 43
  • Computer Vision and Pattern Recognition 199
  • Safety, Risk, Reliability and Quality 63
  • Management Science and Operations Research 76
Replace C. Patvardhan with:
C. Patvardhan India
Volker Lohweg Germany
Krishnamurthy Dvijotham United States
Fabian Moerchen United States
Pierre Valin Canada
Sukhamay Kundu United States
Dzung T. Phan United States
P. Vannoorenberghe France
Dazhi Wang China
Tom Downs relative to C. Patvardhan India C. Patvardhan's profile →
Citations per field
00.5×2×3.1×
C. Patvardhan · 1×
Citations per year

Countries citing papers authored by Tom Downs

Since Specialization
Citations

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

Fields of papers citing papers by Tom Downs

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Tom Downs, 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 Tom Downs Line = papers co-authored together Tom Downs links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2002159
2 199372
3
Real-valued evolutionary optimization using a flexible probability density estimator
199960
4
General cost functions for support vector regression.
199858
5
Evaluation of support vector machine based forecasting tool in electricity price forecasting for Australian national electricity market participants
200343
6 197841
7 199231
8 200330
9 199829
10
Support Vector methods in learning and feature extraction
199825
11 199213
12 200413
13
A modified particle filter for simultaneous robot localization and landmark tracking in an indoor environment
200413
14
Support vector machine based electricity price forecasting for electricity markets utilising projected assessment of system adequacy data
200312
15 200410
16 19919
17 20037
18 20005
19 20025
20 19954

About Tom Downs

Tom Downs is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Management Science and Operations Research, Software and Safety, Risk, Reliability and Quality, having authored 48 papers that have together received 685 indexed citations. Recurring topics across this work include Neural Networks and Applications (18 papers), Face and Expression Recognition (7 papers), Metaheuristic Optimization Algorithms Research (6 papers), Control Systems and Identification (5 papers), Machine Learning and ELM (5 papers), Reliability and Maintenance Optimization (4 papers), Stock Market Forecasting Methods (4 papers) and Fuzzy Logic and Control Systems (4 papers). The work is most often cited by research in Artificial Intelligence (412 citations), Software (43 citations), Computer Vision and Pattern Recognition (199 citations), Safety, Risk, Reliability and Quality (63 citations) and Management Science and Operations Research (76 citations). Tom Downs has collaborated with scholars based in Australia, United States and Germany. Frequent co-authors include Kevin E. Gates, Marcus Gallagher, Marcus R. Frean, N.J. Redding, Adam P. Kowalczyk, Steven R. Young, Tapan Kumar Saha, Bernhard Schölkopf, K-R Müller and AJ Smola. Their work appears in journals such as IEEE Transactions on Reliability, Neural Networks, The American Statistician, Neurocomputing and Electronics 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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