Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Penalising Model Component Complexity: A Principled, Practical Approach to Constructing Priors
2017622 citationsDaniel Simpson, Håvard Rue et al.Statistical Scienceprofile →
Visualization in Bayesian Workflow
2019604 citationsDaniel Simpson, Aki Vehtari et al.profile →
Bayesian Computing with INLA: A Review
2017457 citationsHåvard Rue, Andrea Riebler et al.profile →
Bayesian computing with INLA: New features
2013402 citationsThiago G. Martins, Daniel Simpson et al.Computational Statistics & Data Analysisprofile →
The Prior Can Often Only Be Understood in the Context of the Likelihood
2017302 citationsAndrew Gelman, Daniel Simpson et al.profile →
Global and regional causes of maternal deaths 2009–20: a WHO systematic analysis
202539 citationsJenny A. Cresswell, Monica Alexander et al.The Lancet Global Healthprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
Countries citing papers authored by Daniel Simpson
Since
Specialization
Citations
This map shows the geographic impact of Daniel Simpson'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 Daniel Simpson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Simpson more than expected).
This network shows the impact of papers produced by Daniel Simpson. 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 Daniel Simpson. The network helps show where Daniel Simpson may publish in the future.
Co-authorship network of co-authors of Daniel Simpson
This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Simpson.
A scholar is included among the top collaborators of Daniel Simpson 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 Daniel Simpson. Daniel Simpson 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.
Cresswell, Jenny A., Monica Alexander, Doris Chou, et al.. (2025). Global and regional causes of maternal deaths 2009–20: a WHO systematic analysis. The Lancet Global Health. 13(4). e626–e634.39 indexed citations breakdown →
Mengersen, Kerrie, et al.. (2020). Combining Opinions for Use in Bayesian Networks: A Measurement Error Approach. QUT ePrints (Queensland University of Technology).2 indexed citations
9.
Simpson, Daniel, et al.. (2020). Asynchronous Gibbs Sampling.. International Conference on Artificial Intelligence and Statistics. 144–154.3 indexed citations
Yao, Yuling, Aki Vehtari, Daniel Simpson, & Andrew Gelman. (2018). Yes, but did it work?: Evaluating variational inference. Aaltodoc (Aalto University). 5581–5590.2 indexed citations
Fuglstad, Geir‐Arne, Daniel Simpson, Finn Lindgren, & Håvard Rue. (2015). Interpretable Priors for Hyperparameters for Gaussian Random Fields. arXiv (Cornell University).9 indexed citations
Girolami, Mark, Anne-Marie Lyne, Heiko Strathmann, Daniel Simpson, & Yves F. Atchadé. (2013). Playing Russian Roulette with Intractable Likelihoods. arXiv (Cornell University).9 indexed citations
17.
Martins, Thiago G., Daniel Simpson, Finn Lindgren, & Håvard Rue. (2013). Bayesian computing with INLA: New features. Computational Statistics & Data Analysis. 67. 68–83.402 indexed citations breakdown →
18.
Cameletti, Michela, Finn Lindgren, Daniel Simpson, & Håvard Rue. (2011). Using the SPDE approach for air qualitymapping in Piemonte region.2 indexed citations
19.
Simpson, Daniel, Ian Turner, & A. N. Pettitt. (2008). Sampling from a Gaussian Markov random field conditioned on linear constraints. The ANZIAM Journal. 48.1 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.