Maxime Turgeon

411 total citations
12 papers, 141 citations indexed

About

Maxime Turgeon is a scholar working on Statistics and Probability, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Maxime Turgeon has authored 12 papers receiving a total of 141 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Statistics and Probability, 3 papers in Artificial Intelligence and 2 papers in Computer Networks and Communications. Recurrent topics in Maxime Turgeon's work include Statistical Methods and Bayesian Inference (3 papers), Statistical Methods and Inference (3 papers) and Advanced Causal Inference Techniques (2 papers). Maxime Turgeon is often cited by papers focused on Statistical Methods and Bayesian Inference (3 papers), Statistical Methods and Inference (3 papers) and Advanced Causal Inference Techniques (2 papers). Maxime Turgeon collaborates with scholars based in Canada, Chile and United States. Maxime Turgeon's co-authors include Celia M.T. Greenwood, Omar Ahmad, Robert Sladek, Muhammad Mujammami, J. Brent Richards, Vincenzo Forgetta, John Morris, George Thanassoulis, James B. Meigs and Aaron Leong and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Journal of the American Geriatrics Society.

In The Last Decade

Maxime Turgeon

9 papers receiving 141 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Maxime Turgeon Canada	5	66	42	39	27	22	12	141
Manickam Chidambaram India	8	58 0.9×	34 0.8×	81 2.1×	13 0.5×	11 0.5×	11	196
Timothy D. Majarian United States	8	79 1.2×	36 0.9×	57 1.5×	24 0.9×	7 0.3×	12	151
Naoya Ichimura Japan	8	17 0.3×	29 0.7×	60 1.5×	13 0.5×	20 0.9×	14	168
Sarah Ellul Malta	4	32 0.5×	11 0.3×	79 2.0×	22 0.8×	7 0.3×	10	146
Philip Schroeder United States	6	45 0.7×	28 0.7×	19 0.5×	28 1.0×	13 0.6×	10	99
Diane Lena France	7	21 0.3×	29 0.7×	32 0.8×	21 0.8×	50 2.3×	16	175
Peter Yong United Kingdom	8	22 0.3×	64 1.5×	61 1.6×	19 0.7×	5 0.2×	9	272
Maria Teresa Martínez Larrad Spain	4	94 1.4×	43 1.0×	21 0.5×	54 2.0×	5 0.2×	5	194
Jason Schairer United States	6	38 0.6×	21 0.5×	13 0.3×	17 0.6×	25 1.1×	12	96

Countries citing papers authored by Maxime Turgeon

Since Specialization

Citations

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

Fields of papers citing papers by Maxime Turgeon

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maxime Turgeon

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

All Works

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12 of 12 papers shown

Quan, Samuel, et al.. (2025). Network Analyses to Explore Comorbidities Among Older Adults Living With Dementia. Journal of the American Geriatrics Society. 73(4). 1168–1178. 1 indexed citations

Turgeon, Maxime, et al.. (2024). A comprehensive study of auto-encoders for anomaly detection: Efficiency and trade-offs. SHILAP Revista de lepidopterología. 17. 100572–100572. 7 indexed citations

Turgeon, Maxime, et al.. (2024). Case-Base Neural Network: Survival analysis with time-varying, higher-order interactions. SHILAP Revista de lepidopterología. 16. 100535–100535.

Nickel, Nathan, et al.. (2024). The validity of electronic health data for measuring smoking status: a systematic review and meta-analysis. BMC Medical Informatics and Decision Making. 24(1). 33–33. 1 indexed citations

Muthukumarana, Saman, et al.. (2024). Parsimonious Bayesian model-based clustering with dissimilarities. SHILAP Revista de lepidopterología. 15. 100528–100528.

Turgeon, Maxime, et al.. (2024). Disentangled Conditional Variational Autoencoder for Unsupervised Anomaly Detection. 138–143.

Bhatnagar, Sahir, et al.. (2022). casebase: An Alternative Framework for Survival Analysis and Comparison of Event Rates. The R Journal. 14(3). 59–79. 2 indexed citations

Farkas, Carlos, et al.. (2021). A Novel SARS-CoV-2 Viral Sequence Bioinformatic Pipeline Has Found Genetic Evidence That the Viral 3′ Untranslated Region (UTR) Is Evolving and Generating Increased Viral Diversity. Frontiers in Microbiology. 12. 665041–665041. 17 indexed citations

Turgeon, Maxime. (2018). Distribution of Largest Root for Single and Double Wishart Settings [R package rootWishart version 0.4.1]. 1 indexed citations

10.

Turgeon, Maxime, Karim Oualkacha, Antonio Ciampi, et al.. (2016). Principal component of explained variance: An efficient and optimal data dimension reduction framework for association studies. Statistical Methods in Medical Research. 27(5). 1331–1350. 8 indexed citations

11.

Ahmad, Omar, John Morris, Muhammad Mujammami, et al.. (2015). A Mendelian randomization study of the effect of type-2 diabetes on coronary heart disease. Nature Communications. 6(1). 7060–7060. 99 indexed citations

12.

Wang, Yishu, et al.. (2015). The perils of quasi‐likelihood information criteria. Stat. 4(1). 246–254. 5 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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