Matias Quiroz

464 citations
13 papers · 170 indexed · h-index 7

Matias Quiroz

12 papers receiving 168 citations

Peers

Matias Quiroz
Comparison fields: 5 of 60
  • Statistics and Probability 80
  • Artificial Intelligence 81
  • Oceanography 19
  • Finance 10
  • Statistics, Probability and Uncertainty 7
Replace James Balamuta with:
James Balamuta United States
John Verzani United States
Shogo Kato Japan
George P. Yanev United States
A. J. Lee New Zealand
Clare A. McGrory Australia
Stephane S. Robin France
Ci‐Ren Jiang Taiwan
Ι. Παπαγεωργίου Greece
F. Garwood United Kingdom
Matias Quiroz relative to James Balamuta United States James Balamuta's profile →
Citations per field
00.5×4.8×
James Balamuta · 1×
Citations per year

Countries citing papers authored by Matias Quiroz

Since Specialization
Citations

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

Fields of papers citing papers by Matias Quiroz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 15 scholars most cited alongside Matias Quiroz, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Matias Quiroz Line = papers co-authored together Matias Quiroz links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1 20220
2 20226
3 20214
4 20202
5 202024
6
On some variance reduction properties of the reparameterization trick.
20181
7
Subsampling MCMC - A review for the survey statistician
20181
8 201869
9 20189
10 201720
11 20159
12 20133
13 200722

About Matias Quiroz

Matias Quiroz is a scholar working on Statistics and Probability, Artificial Intelligence and Modeling and Simulation, having authored 13 papers that have together received 170 indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (4 papers), Markov Chains and Monte Carlo Methods (4 papers), Statistical Methods and Bayesian Inference (3 papers), Statistical Methods and Inference (3 papers), Machine Learning and Algorithms (2 papers), Financial Risk and Volatility Modeling (2 papers), Blind Source Separation Techniques (2 papers) and Algorithms and Data Compression (2 papers). The work is most often cited by research in Statistics and Probability (80 citations), Artificial Intelligence (81 citations) and Oceanography (19 citations). Matias Quiroz has collaborated with scholars based in Australia, Sweden and Singapore. Frequent co-authors include Mattias Villani, Robert Kohn, Minh‐Ngoc Tran, Gregory F. Grether, Kimberly Y. Lin, Gita R. Kolluru, Scott A. Sisson, Matthew Adams, Len McKenzie and Catherine Collier. Their work appears in journals such as Journal of Computational and Graphical Statistics, Bayesian Analysis, Functional Ecology, Environmental Modelling & Software and Journal of the American Statistical Association.

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