Sara Martino

6.3k citations
28 papers · 3.9k indexed · 1 hit paper · h-index 13

Sara Martino

26 papers receiving 3.8k citations

Hit Papers

Approximate Bayesian Inference for Latent Gaussian models...2009202620142020200910002.0k3.0k

Peers

Sara Martino
Comparison fields: 5 of 181
  • Statistics and Probability 811
  • Economics and Econometrics 681
  • Global and Planetary Change 567
  • Artificial Intelligence 558
  • Ecology 545
Replace Daniel Simpson with:
Daniel Simpson United Kingdom
Nicolás Chopin France
Finn Lindgren United Kingdom
Andrea Riebler Norway
Rana Moyeed United Kingdom
Virgilio Gómez‐Rubio Spain
Sigrunn H. Sørbye Norway
Leonhard Held Switzerland
Brian J. Reich United States
Michela Cameletti Italy
Sara Martino relative to Daniel Simpson United Kingdom Daniel Simpson's profile →
Citations per field
00.5×2.7×
Daniel Simpson · 1×
Citations per year

Countries citing papers authored by Sara Martino

Since Specialization
Citations

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

Fields of papers citing papers by Sara Martino

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sara Martino

This figure shows the co-authorship network connecting the top 25 collaborators of Sara Martino. A scholar is included among the top collaborators of Sara Martino 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 Sara Martino. Sara Martino 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 2
3 4
4 0
5 3
6 1
7 1
8 3
9 4
10 6
11 6
12 2
13 22
14 58
15 44
16 19
17 69
18
Approximate Bayesian Inference for Latent Gaussian models by using Integrated Nested Laplace Approximationsbreakdown →
3281
19
Approximate Bayesian Inference for Multivariate Stochastic Volatility Models
2
20
Approximate Bayesian Inference for Latent Gaussian Models
18

About Sara Martino

Sara Martino is a scholar working on Statistics and Probability, Environmental Engineering and Global and Planetary Change, having authored 28 papers that have together received 3.9k indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (9 papers), Soil Geostatistics and Mapping (8 papers) and Bayesian Methods and Mixture Models (6 papers). The work is most often cited by research in Statistics and Probability (811 citations), Ecological Modeling (249 citations) and Modeling and Simulation (258 citations). Sara Martino has collaborated with scholars based in Norway, Italy and Saudi Arabia. Frequent co-authors include Håvard Rue, Nicolás Chopin, Steven G. Cumming, Julien Béguin, Jo Eidsvik, Henrik Jensen, Ingelin Steinsland, Sigrunn H. Sørbye, Janine Illian and Justin M. J. Travis. Their work appears in journals such as Atmospheric Environment, Journal of the Royal Statistical Society Series B (Statistical Methodology) and Accident Analysis & Prevention.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026