David J. Nott
Impact in
- Statistics and Probability top 0.5%
- Statistical Methods and Inference
- Statistical Methods and Bayesian Inference
- Markov Chains and Monte Carlo Methods
- Water Science and Technology top 5%
- Hydrology and Watershed Management Studies
Papers in
-
- Statistical Methods and Inference 41
- Statistical Methods and Bayesian Inference 38
- Markov Chains and Monte Carlo Methods 20
-
- Bayesian Methods and Mixture Models 44
- Gaussian Processes and Bayesian Inference 24
- Co-authors
- Lucy MarshallAshish SharmaRobert KohnMinh‐Ngoc TranChristopher DrovandiChenlei LengAnthony Y. C. KukScott A. Sisson
- Journals
- Journal of Computational and Graphical Statistics (17 papers)Statistics and Computing (10 papers)Computational Statistics & Data Analysis (6 papers)Journal of the American Statistical Association (6 papers)Water Resources Research (5 papers)
- Partner nations
- SingaporeAustraliaUnited States
In The Last Decade
David J. Nott
98 papers receiving 1.9k citations
Peers
Comparison fields: 5 of 142
- Statistics and Probability 756
- Water Science and Technology 379
- Environmental Engineering 326
- Artificial Intelligence 716
- Statistics, Probability and Uncertainty 114
Countries citing papers authored by David J. Nott
This map shows the geographic impact of David J. Nott'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 David J. Nott with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David J. Nott more than expected).
Fields of papers citing papers by David J. Nott
This network shows the impact of papers produced by David J. Nott. 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 David J. Nott. The network helps show where David J. Nott may publish in the future.
Co-authors
The 25 scholars most cited alongside David J. Nott, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 2 | |
| 4 | 2024 | 0 | |
| 5 | 2023 | 3 | |
| 6 | 2022 | 21 | |
| 7 | 2021 | 3 | |
| 8 | 2020 | 13 | |
| 9 | 2020 | 18 | |
| 10 | 2018 | 15 | |
| 11 | New Insights into History Matching via Sequential Monte Carlo | 2017 | 1 |
| 12 | 2016 | 6 | |
| 13 | 2013 | 86 | |
| 14 | 2011 | 16 | |
| 15 | 2009 | 14 | |
| 16 | 2009 | 19 | |
| 17 | 2009 | 79 | |
| 18 | 2006 | 12 | |
| 19 | 2006 | 2 | |
| 20 | Modelling the Catchment via Mixtures: Issues of Model Specification and Validation | 2005 | 2 |
About David J. Nott
David J. Nott is a scholar working on Statistics and Probability, Artificial Intelligence, Statistics, Probability and Uncertainty, Environmental Engineering and Water Science and Technology, having authored 105 papers that have together received 2.0k indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (44 papers), Statistical Methods and Inference (41 papers), Statistical Methods and Bayesian Inference (38 papers), Gaussian Processes and Bayesian Inference (24 papers), Markov Chains and Monte Carlo Methods (20 papers), Soil Geostatistics and Mapping (8 papers), Hydrology and Watershed Management Studies (8 papers) and Hydrology and Drought Analysis (7 papers). The work is most often cited by research in Statistics and Probability (756 citations), Water Science and Technology (379 citations), Environmental Engineering (326 citations), Artificial Intelligence (716 citations) and Statistics, Probability and Uncertainty (114 citations). David J. Nott has collaborated with scholars based in Singapore, Australia and United States. Frequent co-authors include Lucy Marshall, Ashish Sharma, Robert Kohn, Minh‐Ngoc Tran, Christopher Drovandi, Chenlei Leng, Anthony Y. C. Kuk, Scott A. Sisson, Anthony Lee and Jason Brown. Their work appears in journals such as Journal of Computational and Graphical Statistics, Statistics and Computing, Computational Statistics & Data Analysis, Journal of the American Statistical Association and Water Resources Research.
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.