Antonio Canale

908 total citations
57 papers, 498 citations indexed

About

Antonio Canale is a scholar working on Statistics and Probability, Artificial Intelligence and Automotive Engineering. According to data from OpenAlex, Antonio Canale has authored 57 papers receiving a total of 498 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Statistics and Probability, 23 papers in Artificial Intelligence and 10 papers in Automotive Engineering. Recurrent topics in Antonio Canale's work include Bayesian Methods and Mixture Models (20 papers), Statistical Methods and Bayesian Inference (15 papers) and Statistical Methods and Inference (15 papers). Antonio Canale is often cited by papers focused on Bayesian Methods and Mixture Models (20 papers), Statistical Methods and Bayesian Inference (15 papers) and Statistical Methods and Inference (15 papers). Antonio Canale collaborates with scholars based in Italy, United States and Brazil. Antonio Canale's co-authors include David B. Dunson, Igor Prünster, Simone Vantini, Stefano Gipponi, Andrea Pilotto, Francesco Marra, Alessandro Padovani, Michela Bezzi, Viviana Cristillo and Nicola Zoppi and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the American Statistical Association and Water Resources Research.

In The Last Decade

Antonio Canale

55 papers receiving 485 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Antonio Canale Italy 12 159 153 123 50 48 57 498
Polychronis Εconomou Greece 9 123 0.8× 65 0.4× 14 0.1× 22 0.4× 65 1.4× 60 362
Glaura C. Franco Brazil 12 59 0.4× 28 0.2× 84 0.7× 4 0.1× 27 0.6× 35 372
Daniel Sabanés Bové Switzerland 13 167 1.1× 64 0.4× 20 0.2× 33 0.7× 10 0.2× 25 539
María Amalia Jácome Spain 12 149 0.9× 63 0.4× 34 0.3× 4 0.1× 36 0.8× 46 549
Luigi Ippoliti Italy 10 23 0.1× 35 0.2× 100 0.8× 3 0.1× 30 0.6× 45 387
Robert Maidstone United Kingdom 10 62 0.4× 17 0.1× 4 0.0× 11 0.2× 30 0.6× 24 489
Jonathan D. Rosenblatt Israel 10 25 0.2× 34 0.2× 16 0.1× 3 0.1× 29 0.6× 23 259
Elvan Ceyhan Türkiye 12 26 0.2× 40 0.3× 20 0.2× 6 0.1× 20 0.4× 47 405
Piero Quatto Italy 10 41 0.3× 64 0.4× 22 0.2× 10 0.2× 2 0.0× 44 507
Aaron Fisher United States 7 39 0.2× 101 0.7× 4 0.0× 12 0.2× 7 0.1× 13 357

Countries citing papers authored by Antonio Canale

Since Specialization
Citations

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

Fields of papers citing papers by Antonio Canale

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Antonio Canale

This figure shows the co-authorship network connecting the top 25 collaborators of Antonio Canale. A scholar is included among the top collaborators of Antonio Canale 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 Antonio Canale. Antonio Canale 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
1.
Pilotto, Andrea, Nicholas J. Ashton, Stefano Gipponi, et al.. (2024). Plasma NfL, GFAP, amyloid, and p-tau species as Prognostic biomarkers in Parkinson’s disease. Journal of Neurology. 271(12). 7537–7546. 16 indexed citations
2.
Canale, Antonio, et al.. (2024). Accelerated Structured Matrix Factorization. Journal of Computational and Graphical Statistics. 33(3). 917–927. 1 indexed citations
3.
Borga, Marco, Giorgia Fosser, Antonio Canale, et al.. (2024). A Method to Assess and Explain Changes in Sub‐Daily Precipitation Return Levels From Convection‐Permitting Simulations. Water Resources Research. 60(5). 21 indexed citations
4.
Marra, Francesco, Marika Koukoula, Antonio Canale, & Nadav Peleg. (2024). Predicting extreme sub-hourly precipitation intensification based on temperature shifts. Hydrology and earth system sciences. 28(2). 375–389. 24 indexed citations
5.
Canale, Antonio, et al.. (2023). Inner spike and slab Bayesian nonparametric models. BOA (University of Milano-Bicocca). 1 indexed citations
6.
Canale, Antonio, et al.. (2023). A hierarchical Bayesian non‐asymptotic extreme value model for spatial data. Environmetrics. 34(7). 2 indexed citations
7.
Canale, Antonio, et al.. (2023). Semiparametric Functional Factor Models with Bayesian Rank Selection. Bayesian Analysis. 18(4). 6 indexed citations
8.
Canale, Antonio, et al.. (2022). Importance conditional sampling for Pitman–Yor mixtures. Statistics and Computing. 32(3). 5 indexed citations
9.
Cristillo, Viviana, Andrea Pilotto, Stefano Cotti Piccinelli, et al.. (2022). Premorbid vulnerability and disease severity impact on Long-COVID cognitive impairment. Aging Clinical and Experimental Research. 34(1). 257–260. 18 indexed citations
10.
Canale, Antonio, et al.. (2021). Multiscale stick-breaking mixture models. IRIS Research product catalog (Sapienza University of Rome). 2 indexed citations
11.
Pilotto, Andrea, Viviana Cristillo, Stefano Cotti Piccinelli, et al.. (2021). Long-term neurological manifestations of COVID-19: prevalence and predictive factors. Neurological Sciences. 42(12). 4903–4907. 101 indexed citations
12.
13.
Canale, Antonio, et al.. (2019). Importance conditional sampling for Bayesian nonparametric mixtures. arXiv (Cornell University). 2 indexed citations
14.
Durante, Daniele, et al.. (2018). A nested expectation–maximization algorithm for latent class models with covariates. Statistics & Probability Letters. 146. 97–103. 2 indexed citations
15.
Canale, Antonio, et al.. (2018). Quantifying prediction uncertainty for functional-and-scalar to functional autoregressive models under shape constraints. Journal of Multivariate Analysis. 170. 221–231. 7 indexed citations
16.
Canale, Antonio & Pierpaolo De Blasi. (2017). Posterior asymptotics of nonparametric location-scale mixtures for multivariate density estimation. Institutional Research Information System University of Turin (University of Turin). 12 indexed citations
17.
Wang, Ye, Antonio Canale, & David B. Dunson. (2016). Scalable geometric density estimation. International Conference on Artificial Intelligence and Statistics. 51. 857–865. 1 indexed citations
18.
Canale, Antonio & David B. Dunson. (2011). Bayesian Kernel Mixtures for Counts. Journal of the American Statistical Association. 106(496). 1528–1539. 50 indexed citations
19.
Fernandes, Dirceu Maximino, et al.. (1998). Performance Charts: A Complete Analysis of Heavy Vehicle Braking Performance. SAE technical papers on CD-ROM/SAE technical paper series. 1.
20.
Fernandes, Dirceu Maximino, et al.. (1995). A Study of the Influence of the Brake Force Distribution on the Directional Stability of Heavy Vehicles During the Brailing Process. SAE technical papers on CD-ROM/SAE technical paper series. 1. 1 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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