Trevor Campbell
- Statistical and Nonlinear Physics top 5%
- Artificial Intelligence top 10%
- Mechanical Engineering
- Mechanics of Materials
- Electrical and Electronic Engineering
- Co-authors
- Reza VaziriAnoush PoursartipSina Amini NiakiEhsan HaghighatJonathan P. HowTamara BroderickJonathan H. HugginsBrian Kulis
- Topics
- Gaussian Processes and Bayesian Inference (10 papers)Bayesian Methods and Mixture Models (7 papers)Statistical Methods and Inference (5 papers)
- Cited by
- Statistical and Nonlinear PhysicsArtificial IntelligenceStatistics, Probability and Uncertainty
- Journals
- Computer Methods in Applied Mechanics and EngineeringComposites Part A Applied Science and ManufacturingJournal of Machine Learning Research
- Partner nations
- CanadaUnited StatesLuxembourg
In The Last Decade
Trevor Campbell
21 papers receiving 333 citations
Hit Papers
Peers
Comparison fields: 5 of 69
- Statistical and Nonlinear Physics 118
- Artificial Intelligence 98
- Mechanical Engineering 62
- Mechanics of Materials 55
- Electrical and Electronic Engineering 43
Countries citing papers authored by Trevor Campbell
This map shows the geographic impact of Trevor Campbell'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 Trevor Campbell with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Trevor Campbell more than expected).
Fields of papers citing papers by Trevor Campbell
This network shows the impact of papers produced by Trevor Campbell. 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 Trevor Campbell. The network helps show where Trevor Campbell may publish in the future.
Co-authorship network of co-authors of Trevor Campbell
This figure shows the co-authorship network connecting the top 25 collaborators of Trevor Campbell. A scholar is included among the top collaborators of Trevor Campbell 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 Trevor Campbell. Trevor Campbell 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 | 2 | |
| 3 | 2 | |
| 4 | 2 | |
| 5 | 0 | |
| 6 | 7 | |
| 7 | 1 | |
| 8 | Finite mixture models are typically inconsistent for the number of components | 1 |
| 9 | Validated Variational Inference via Practical Posterior Error Bounds | 4 |
| 10 | Automated Scalable Bayesian Inference via Hilbert Coresets | 22 |
| 11 | Practical Posterior Error Bounds from Variational Objectives | 1 |
| 12 | Scalable Gaussian Process Inference with Finite-data Mean and Variance Guarantees | 1 |
| 13 | 3 | |
| 14 | Coresets for Scalable Bayesian Logistic Regression | 11 |
| 15 | 33 | |
| 16 | Decentralized Variational Bayesian Inference. | 2 |
| 17 | 18 | |
| 18 | 7 | |
| 19 | Planning under Uncertainty using Nonparametric Bayesian Models | 2 |
| 20 | 2 |
About Trevor Campbell
Trevor Campbell is a scholar working on Statistics and Probability, Artificial Intelligence and Statistical and Nonlinear Physics, having authored 24 papers that have together received 364 indexed citations. Recurring topics across this work include Gaussian Processes and Bayesian Inference (10 papers), Bayesian Methods and Mixture Models (7 papers) and Statistical Methods and Inference (5 papers). The work is most often cited by research in Statistical and Nonlinear Physics (118 citations), Artificial Intelligence (98 citations) and Statistics, Probability and Uncertainty (19 citations). Trevor Campbell has collaborated with scholars based in Canada, United States and Luxembourg. Frequent co-authors include Reza Vaziri, Anoush Poursartip, Sina Amini Niaki, Ehsan Haghighat, Jonathan P. How, Tamara Broderick, Jonathan H. Huggins, Brian Kulis, Miao Liu and Lawrence Carin. Their work appears in journals such as Computer Methods in Applied Mechanics and Engineering, Composites Part A Applied Science and Manufacturing and Journal of Machine Learning 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.