Ben Calderhead
Impact in
- Artificial Intelligence top 0.1%
- Topic Modeling
- Domain Adaptation and Few-Shot Learning
- Natural Language Processing Techniques
- Anomaly Detection Techniques and Applications
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- Advanced Neural Network Applications
- Multimodal Machine Learning Applications
- Generative Adversarial Networks and Image Synthesis
Papers in
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- Markov Chains and Monte Carlo Methods 8
- Statistical Methods and Inference 2
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- Gaussian Processes and Bayesian Inference 6
- Co-authors
- Onur Teymur (3 shared papers)Mark Girolami (11 shared papers)Neil D. Lawrence (1 shared paper)Derek Groen (1 shared paper)Michael Epstein (2 shared papers)Nicole Radde (1 shared paper)Maurizio Filippone (3 shared papers)Lucia G. Sivilotti (2 shared papers)
- Journals
- Proceedings of the National Academy of Sciences (1 paper)Journal of the Royal Statistical Society Series B (Statistical Methodology) (1 paper)Computational Statistics & Data Analysis (1 paper)BMC Bioinformatics (1 paper)Bayesian Analysis (1 paper)
- Partner nations
- United KingdomUnited StatesMalaysia
In The Last Decade
Ben Calderhead
23 papers receiving 12.2k citations
Ben Calderhead's Hit Papers
Peers
Comparison fields: 5 of 221
- Artificial Intelligence 5.2k
- Computer Vision and Pattern Recognition 3.0k
- Health Informatics 148
- Statistics and Probability 660
- Computational Mathematics 32
Countries citing papers authored by Ben Calderhead
This map shows the geographic impact of Ben Calderhead'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 Ben Calderhead with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ben Calderhead more than expected).
Fields of papers citing papers by Ben Calderhead
This network shows the impact of papers produced by Ben Calderhead. 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 Ben Calderhead. The network helps show where Ben Calderhead may publish in the future.
Co-authors
The 25 scholars most cited alongside Ben Calderhead, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Advances in Neural Information Processing Systems 29 Hit paper breakdown → | 2016 | 11300 |
| 2 | Riemann Manifold Langevin and Hamiltonian Monte Carlo Methods Hit paper breakdown → | 2011 | 777 |
| 3 | 2009 | 84 | |
| 4 | Accelerating Bayesian Inference over Nonlinear Differential Equations with Gaussian Processes | 2008 | 80 |
| 5 | 2014 | 72 | |
| 6 | 2011 | 30 | |
| 7 | 2011 | 28 | |
| 8 | 2014 | 21 | |
| 9 | 2014 | 21 | |
| 10 | 2016 | 18 | |
| 11 | 2015 | 18 | |
| 12 | Bayesian Uncertainty Quantification for Differential Equations | 2013 | 13 |
| 13 | 2007 | 11 | |
| 14 | 2013 | 8 | |
| 15 | Sparse Approximate Manifolds for Differential Geometric MCMC | 2012 | 6 |
| 16 | Implicit Probabilistic Integrators for ODEs | 2018 | 4 |
| 17 | 2017 | 4 | |
| 18 | 2016 | 4 | |
| 19 | 2010 | 4 | |
| 20 | 2020 | 3 |
About Ben Calderhead
Ben Calderhead is a scholar working on Statistics and Probability, Artificial Intelligence, Molecular Biology, Statistical and Nonlinear Physics and Spectroscopy, having authored 23 papers that have together received 12.5k indexed citations. Recurring topics across this work include Markov Chains and Monte Carlo Methods (8 papers), Gaussian Processes and Bayesian Inference (6 papers), Protein Structure and Dynamics (4 papers), Mass Spectrometry Techniques and Applications (3 papers), Statistical Methods and Inference (2 papers), Reservoir Engineering and Simulation Methods (2 papers), Model Reduction and Neural Networks (2 papers) and Genetics, Bioinformatics, and Biomedical Research (1 paper). The work is most often cited by research in Artificial Intelligence (5.2k citations), Computer Vision and Pattern Recognition (3.0k citations), Health Informatics (148 citations), Statistics and Probability (660 citations) and Computational Mathematics (32 citations). Ben Calderhead has collaborated with scholars based in United Kingdom, United States and Malaysia. Frequent co-authors include Onur Teymur, Mark Girolami, Neil D. Lawrence, Derek Groen, Michael Epstein, Nicole Radde, Maurizio Filippone, Lucia G. Sivilotti, Mike Christie and David A. Campbell. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of the Royal Statistical Society Series B (Statistical Methodology), Computational Statistics & Data Analysis, BMC Bioinformatics and Bayesian Analysis.
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.