Layne T. Watson

391 papers receiving 8.9k citations

Hit Papers

Numerical Continuation Methods--An Introduction.19922026200320141992200400600

Peers

Layne T. Watson
Comparison fields: 5 of 175
  • Computational Theory and Mathematics 3.4k
  • Numerical Analysis 1.7k
  • Civil and Structural Engineering 1.6k
  • Computational Mechanics 1.5k
  • Statistics, Probability and Uncertainty 1.4k
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Countries citing papers authored by Layne T. Watson

Since Specialization
Citations

This map shows the geographic impact of Layne T. Watson'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 Layne T. Watson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Layne T. Watson more than expected).

Fields of papers citing papers by Layne T. Watson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Layne T. Watson. 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 Layne T. Watson. The network helps show where Layne T. Watson may publish in the future.

Co-authorship network of co-authors of Layne T. Watson

This figure shows the co-authorship network connecting the top 25 collaborators of Layne T. Watson. A scholar is included among the top collaborators of Layne T. Watson based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Layne T. Watson. Layne T. Watson is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 6
3 0
4 2
5 2
6 3
7 3
8 1
9 5
10
A Novel Computation-to-core Mapping Scheme for Robust Facet Image Modeling on GPUs.
3
11 5
12
Semi-Supervised Learning of Hidden Markov\nModels via a Homotopy Method
19
13 6
14
Sensitivity Analysis of Internal Mat Environment during Hot-Pressing
14
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Simulation of the Internal Conditions During The Hot-Pressing Process
32
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A Fully Distribute Parallel Global Search Algorithm.
2
17 4
18 2
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A Homotopy Method for Solving Riccati Equations on a Shared Memory Parallel Computer.
3
20
A Survey of Probability-One Homotopy Methods for Engineering Optimization
10

About Layne T. Watson

Layne T. Watson is a scholar working on Numerical Analysis, Computational Theory and Mathematics and Statistics, Probability and Uncertainty, having authored 403 papers that have together received 9.7k indexed citations. Recurring topics across this work include Advanced Multi-Objective Optimization Algorithms (77 papers), Probabilistic and Robust Engineering Design (65 papers) and Advanced Optimization Algorithms Research (53 papers). The work is most often cited by research in Numerical Analysis (1.7k citations), Computational Theory and Mathematics (3.4k citations) and Statistics, Probability and Uncertainty (1.4k citations). Layne T. Watson has collaborated with scholars based in United States, Kuwait and Netherlands. Frequent co-authors include Raphael T. Haftka, Eugene L. Allgower, Kurt Georg, Anthony Giunta, Alexander P. Morgan, Robert M. Haralick, Zafer Gürdal, Stephen C. Billups, John E. Renaud and Z. Gürdal. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Automatic Control and Journal of Fluid Mechanics.

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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