David J. Marchette

2.1k total citations
72 papers, 1.3k citations indexed

About

David J. Marchette is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, David J. Marchette has authored 72 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Artificial Intelligence, 15 papers in Computer Vision and Pattern Recognition and 9 papers in Computer Networks and Communications. Recurrent topics in David J. Marchette's work include Bayesian Methods and Mixture Models (11 papers), Neural Networks and Applications (11 papers) and Anomaly Detection Techniques and Applications (10 papers). David J. Marchette is often cited by papers focused on Bayesian Methods and Mixture Models (11 papers), Neural Networks and Applications (11 papers) and Anomaly Detection Techniques and Applications (10 papers). David J. Marchette collaborates with scholars based in United States, Russia and Türkiye. David J. Marchette's co-authors include Carey E. Priebe, John C. Wierman, Youngser Park, John M. Conroy, Edward J. Wegman, Lancelot F. James, Jeffrey L. Solka, Bradley C. Wallet, Diego A. Socolinsky and Vijayan N. Nair and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Technometrics and Pattern Recognition.

In The Last Decade

David J. Marchette

72 papers receiving 1.2k citations

Peers

David J. Marchette

CNC

SNP

CVPR

Anand D. Sarwate United States

Ken A. Hawick New Zealand

Shengrui Wang Canada

Chao Luo China

Alekh Agarwal United States

Junhui Wang United States

Jason D. Lee United States

Ryohei Nakano Japan

Robert Nowak Poland

Anand D. Sarwate United States

David J. Marchette

1.3k ×2.2

948 ×3.1

CNC

89 ×0.3

SNP

159 ×0.9

CVPR

127 ×0.8

Citations per year, relative to David J. Marchette David J. Marchette (= 1×) peers Anand D. Sarwate

Countries citing papers authored by David J. Marchette

Since Specialization

Citations

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

Fields of papers citing papers by David J. Marchette

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David J. Marchette. 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 David J. Marchette. The network helps show where David J. Marchette may publish in the future.

Co-authorship network of co-authors of David J. Marchette

This figure shows the co-authorship network connecting the top 25 collaborators of David J. Marchette. A scholar is included among the top collaborators of David J. Marchette 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 David J. Marchette. David J. Marchette is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Hoover, Randy C., et al.. (2024). TSGCN: A Framework for Hierarchical Graph Representation Learning. IEEE Transactions on Network Science and Engineering. 12(2). 727–737. 2 indexed citations

Mehta, Ketan, et al.. (2021). Neuronal classification from network connectivity via adjacency spectral embedding. Network Neuroscience. 5(3). 1–22. 4 indexed citations

Parks, Allen & David J. Marchette. (2016). Persistent homology in graph power filtrations. Royal Society Open Science. 3(10). 160228–160228. 2 indexed citations

Marchette, David J., et al.. (2016). Dose‐Response Modeling for Inhalational Anthrax in Rabbits Following Single or Multiple Exposures. Risk Analysis. 36(11). 2031–2038. 11 indexed citations

Marchette, David J., et al.. (2015). Utilizing covariates in partially observed networks. International Conference on Information Fusion. 166–172. 1 indexed citations

Athreya, Avanti, Vince Lyzinski, David J. Marchette, et al.. (2013). A limit theorem for scaled eigenvectors of random dot product graphs. arXiv (Cornell University). 3 indexed citations

Mazzuchi, Thomas A., et al.. (2012). Mathematical properties of System Readiness Levels. Systems Engineering. 16(4). 391–400. 16 indexed citations

Marchette, David J., et al.. (2012). Fusion and inference from multiple data sources in a commensurate space. Statistical Analysis and Data Mining The ASA Data Science Journal. 5(3). 187–193. 7 indexed citations

Marchette, David J. & Jeffrey L. Solka. (2011). Fusion of disparate information through joint embeddings. International Conference on Information Fusion. 1–8. 1 indexed citations

10.

Marchette, David J.. (2011). Implicit translation. Wiley Interdisciplinary Reviews Computational Statistics. 4(1). 28–34. 1 indexed citations

11.

Marchette, David J.. (2006). Data Analysis of Asymmetric Structures: Advanced Approaches in Computational Statistics. Technometrics. 48(2). 310–311. 8 indexed citations

12.

Priebe, Christian, David J. Marchette, & D.M. Healy. (2004). Integrated sensing and processing decision trees. IEEE Transactions on Pattern Analysis and Machine Intelligence. 26(6). 699–708. 22 indexed citations

13.

Marchette, David J.. (2004). Random Graphs for Statistical Pattern Recognition. Wiley series in probability and statistics. 30 indexed citations

14.

Marchette, David J.. (2001). Computer Intrusion Detection and Network Monitoring. 40 indexed citations

15.

Priebe, Carey E. & David J. Marchette. (2000). Alternating kernel and mixture density estimates. Computational Statistics & Data Analysis. 35(1). 43–65. 23 indexed citations

16.

Marchette, David J. & Wendy L. Poston. (1999). Local dimensionality reduction. Computational Statistics. 14(4). 469–489. 5 indexed citations

17.

Priebe, Carey E., David J. Marchette, & George W. Rogers. (1997). Semiparametric nonhomogeneity analysis. Journal of Statistical Planning and Inference. 59(1). 45–60. 2 indexed citations

18.

Solka, Jeffrey L., et al.. (1997). <title>Region of interest identification in unmanned aerial vehicle imagery</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 2962. 180–191. 2 indexed citations

19.

Wallet, Bradley C., et al.. (1996). A Genetic Algorithm for Best Subset Selection in Linear Regression. 22 indexed citations

20.

Marchette, David J. & Carey E. Priebe. (1990). The Adaptive Kernel Neural Network. Mathematical and Computer Modelling. 14. 328–333. 7 indexed citations

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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