Chris J. Oates
- Artificial Intelligence top 10%
- Statistics and Probability top 2%
- Molecular Biology
- Statistics, Probability and Uncertainty top 5%
- Statistical and Nonlinear Physics top 10%
- Co-authors
- Mark GirolamiSach MukherjeeNicolás ChopinTheodore PapamarkouFrançois‐Xavier BriolJoe W. GrayT. J. SullivanNial Friel
- Topics
- Gaussian Processes and Bayesian Inference (10 papers)Bayesian Methods and Mixture Models (8 papers)Statistical Methods and Bayesian Inference (8 papers)
- Partner nations
- United KingdomUnited StatesAustralia
In The Last Decade
Chris J. Oates
46 papers receiving 508 citations
Peers
Comparison fields: 5 of 102
- Artificial Intelligence 166
- Statistics and Probability 151
- Molecular Biology 140
- Statistics, Probability and Uncertainty 60
- Statistical and Nonlinear Physics 52
Countries citing papers authored by Chris J. Oates
This map shows the geographic impact of Chris J. Oates'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 Chris J. Oates with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chris J. Oates more than expected).
Fields of papers citing papers by Chris J. Oates
This network shows the impact of papers produced by Chris J. Oates. 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 Chris J. Oates. The network helps show where Chris J. Oates may publish in the future.
Co-authorship network of co-authors of Chris J. Oates
This figure shows the co-authorship network connecting the top 25 collaborators of Chris J. Oates. A scholar is included among the top collaborators of Chris J. Oates 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 Chris J. Oates. Chris J. Oates is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 7 | |
| 3 | 37 | |
| 4 | 1 | |
| 5 | 13 | |
| 6 | Stein's Method Meets Statistics: A Review of Some Recent Developments | 3 |
| 7 | Optimal Quantisation of Probability Measures Using Maximum Mean Discrepancy | 2 |
| 8 | 1 | |
| 9 | 2 | |
| 10 | 16 | |
| 11 | 8 | |
| 12 | Causal Discovery as Semi-Supervised Learning | 1 |
| 13 | NETWORK INFERENCE AND BIOLOGICAL DYNAMICS1 | 28 |
| 14 | 34 | |
| 15 | Control Functionals for Quasi-Monte Carlo Integration | 3 |
| 16 | 58 | |
| 17 | Probabilistic Integration | 2 |
| 18 | 12 | |
| 19 | 20 | |
| 20 | 3 |
About Chris J. Oates
Chris J. Oates is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Numerical Analysis, having authored 48 papers that have together received 527 indexed citations. Recurring topics across this work include Gaussian Processes and Bayesian Inference (10 papers), Bayesian Methods and Mixture Models (8 papers) and Statistical Methods and Bayesian Inference (8 papers). The work is most often cited by research in Statistics and Probability (151 citations), Numerical Analysis (51 citations) and Statistics, Probability and Uncertainty (60 citations). Chris J. Oates has collaborated with scholars based in United Kingdom, United States and Australia. Frequent co-authors include Mark Girolami, Sach Mukherjee, Nicolás Chopin, Theodore Papamarkou, François‐Xavier Briol, Joe W. Gray, T. J. Sullivan, Nial Friel, James E. Korkola and Nora Bayani. Their work appears in journals such as Nature Communications, Journal of the American Statistical Association and Bioinformatics.
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.