Lawrence M. Murray

2.6k total citations
24 papers, 415 citations indexed

About

Lawrence M. Murray is a scholar working on Artificial Intelligence, Control and Systems Engineering and Statistics and Probability. According to data from OpenAlex, Lawrence M. Murray has authored 24 papers receiving a total of 415 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 5 papers in Control and Systems Engineering and 5 papers in Statistics and Probability. Recurrent topics in Lawrence M. Murray's work include Gaussian Processes and Bayesian Inference (6 papers), Target Tracking and Data Fusion in Sensor Networks (6 papers) and Statistical Methods and Bayesian Inference (5 papers). Lawrence M. Murray is often cited by papers focused on Gaussian Processes and Bayesian Inference (6 papers), Target Tracking and Data Fusion in Sensor Networks (6 papers) and Statistical Methods and Bayesian Inference (5 papers). Lawrence M. Murray collaborates with scholars based in Australia, United Kingdom and Sweden. Lawrence M. Murray's co-authors include Anthony Lee, Pierre Jacob, Emlyn Jones, Amos Storkey, Pierre Del Moral, Peter R. Oke, Farhan Rizwi, Laith Yakob, Rosalind M. Eggo and W. John Edmunds and has published in prestigious journals such as IEEE Transactions on Signal Processing, Mechanical Systems and Signal Processing and Journal of Statistical Software.

In The Last Decade

Lawrence M. Murray

22 papers receiving 399 citations

Peers

Lawrence M. Murray

PHEOH

CSE

OCEAN

Wim Wiegerinck Netherlands

Ioannis Andrianakis United Kingdom

Nicholas A. James United States

Mohammad Sajid Saudi Arabia

Mikael Sunnåker Switzerland

Fabien Campillo France

Shiwei Lan United States

Nabendu Pal United States

Eric Forgoston United States

Wim Wiegerinck Netherlands

Lawrence M. Murray

211 ×1.3

8 ×0.1

PHEOH

37 ×0.6

46 ×0.9

CSE

15 ×0.3

OCEAN

Citations per year, relative to Lawrence M. Murray Lawrence M. Murray (= 1×) peers Wim Wiegerinck

Countries citing papers authored by Lawrence M. Murray

Since Specialization

Citations

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

Fields of papers citing papers by Lawrence M. Murray

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lawrence M. Murray. 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 Lawrence M. Murray. The network helps show where Lawrence M. Murray may publish in the future.

Co-authorship network of co-authors of Lawrence M. Murray

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

All Works

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20 of 20 papers shown

Štrumbelj, Erik, Alexandre Bouchard‐Côté, Jukka Corander, et al.. (2024). Past, Present and Future of Software for Bayesian Inference. Statistical Science. 39(1). 14 indexed citations

Ronquist, Fredrik, Viktor Senderov, Johannes Borgström, et al.. (2021). Publisher Correction: Universal probabilistic programming offers a powerful approach to statistical phylogenetics. Communications Biology. 4(1). 354–354.

Ronquist, Fredrik, Viktor Senderov, Johannes Borgström, et al.. (2021). Universal probabilistic programming offers a powerful approach to statistical phylogenetics. Communications Biology. 4(1). 244–244. 13 indexed citations

Murray, Lawrence M., et al.. (2018). Improving the particle filter in high dimensions using conjugate artificial process noise. IFAC-PapersOnLine. 51(15). 670–675. 4 indexed citations

Jacob, Pierre, et al.. (2017). rbi: R Interface to LibBi. London School of Hygiene & Tropical Medicine. 2 indexed citations

Schön, Thomas B., Andreas Svensson, Lawrence M. Murray, & Fredrik Lindsten. (2017). Probabilistic learning of nonlinear dynamical systems using sequential Monte Carlo. Mechanical Systems and Signal Processing. 104. 866–883. 20 indexed citations

Funk, Sebastian, Adam J. Kucharski, Anton Camacho, et al.. (2016). Comparative Analysis of Dengue and Zika Outbreaks Reveals Differences by Setting and Virus. PLoS neglected tropical diseases. 10(12). e0005173–e0005173. 59 indexed citations

Murray, Lawrence M., Anthony Lee, & Pierre Jacob. (2015). Parallel Resampling in the Particle Filter. Journal of Computational and Graphical Statistics. 25(3). 789–805. 71 indexed citations

Murray, Lawrence M.. (2015). Bayesian State-Space Modelling on High-Performance Hardware UsingLibBi. Journal of Statistical Software. 67(10). 21 indexed citations

10.

Moral, Pierre Del & Lawrence M. Murray. (2015). Sequential Monte Carlo with Highly Informative Observations. SIAM/ASA Journal on Uncertainty Quantification. 3(1). 969–997. 17 indexed citations

11.

Clifford, David, Dan Pagendam, Jeff Baldock, et al.. (2014). Rethinking soil carbon modelling: a stochastic approach to quantify uncertainties. Environmetrics. 25(4). 265–278. 14 indexed citations

12.

Murray, Lawrence M., Anthony Lee, & Pierre Jacob. (2013). Rethinking resampling in the particle filter on graphics processing units. arXiv (Cornell University). 4 indexed citations

13.

Moral, Pierre Del, Pierre Jacob, Anthony Lee, Lawrence M. Murray, & Gareth W. Peters. (2013). Feynman-Kac Particle Integration with Geometric Interacting Jumps. Stochastic Analysis and Applications. 31(5). 830–871. 9 indexed citations

14.

Domański, Leszek, Tomasz Bednarz, Timur E. Gureyev, et al.. (2013). Applications of heterogeneous computing in computational and simulation science. International Journal of Computational Science and Engineering. 8(3). 240–240. 3 indexed citations

15.

Murray, Lawrence M.. (2011). GPU Acceleration of Runge-Kutta Integrators. IEEE Transactions on Parallel and Distributed Systems. 23(1). 94–101. 46 indexed citations

16.

Domański, Leszek, Tomasz Bednarz, Timur E. Gureyev, et al.. (2011). Applications of Heterogeneous Computing in Computational and Simulation Science. 27. 382–389. 1 indexed citations

17.

Murray, Lawrence M. & Amos Storkey. (2010). Particle Smoothing in Continuous Time: A Fast Approach via Density Estimation. IEEE Transactions on Signal Processing. 59(3). 1017–1026. 20 indexed citations

18.

Jones, Emlyn, et al.. (2010). A Bayesian approach to state and parameter estimation in a Phytoplankton-Zooplankton model. 59(1SP). 7–16. 32 indexed citations

19.

Murray, Lawrence M. & Amos Storkey. (2007). Continuous Time Particle Filtering for fMRI. Neural Information Processing Systems. 20. 1049–1056. 17 indexed citations

20.

Murray, Lawrence M., et al.. (1992). An accurate PVT model for geothermal fluids as represented by H{sub 2}O-CO{sub 2}-NaCl mixtures. University of North Texas Digital Library (University of North Texas). 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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