Fritz Obermeyer
Impact in
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- Target Tracking and Data Fusion in Sensor Networks
- Bayesian Modeling and Causal Inference
- Gaussian Processes and Bayesian Inference
- Bayesian Methods and Mixture Models
- Adversarial Robustness in Machine Learning
Papers in
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- Target Tracking and Data Fusion in Sensor Networks 3
- Gaussian Processes and Bayesian Inference 2
- Bayesian Modeling and Causal Inference 1
- Logic, Reasoning, and Knowledge 1
- Machine Learning and Data Classification 1
- Anomaly Detection Techniques and Applications 1
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- Time Series Analysis and Forecasting 2
- Co-authors
- Aubrey B. Poore (3 shared papers)Martin Jankowiak (2 shared papers)Scott A. Miller (1 shared paper)Daniel Turek (1 shared paper)Alexander M. Rush (1 shared paper)Abel Rodríguez (1 shared paper)Perry de Valpine (1 shared paper)Duncan Temple Lang (1 shared paper)
- Journals
- arXiv (Cornell University) (1 paper)Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE (2 papers)International Conference on Artificial Intelligence and Statistics (1 paper)International Conference on Machine Learning (1 paper)
- Partner nations
- United StatesIsrael
In The Last Decade
Fritz Obermeyer
6 papers receiving 25 citations
Peers
Comparison fields: 5 of 31
- Computational Mathematics 1
- Artificial Intelligence 24
- Signal Processing 5
- Computer Graphics and Computer-Aided Design 1
- Instrumentation 1
Countries citing papers authored by Fritz Obermeyer
This map shows the geographic impact of Fritz Obermeyer'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 Fritz Obermeyer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fritz Obermeyer more than expected).
Fields of papers citing papers by Fritz Obermeyer
This network shows the impact of papers produced by Fritz Obermeyer. 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 Fritz Obermeyer. The network helps show where Fritz Obermeyer may publish in the future.
Co-authors
The 14 scholars most cited alongside Fritz Obermeyer, 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 | 2003 | 12 | |
| 2 | Pathwise Derivatives Beyond the Reparameterization Trick | 2018 | 7 |
| 3 | 2005 | 6 | |
| 4 | 2004 | 5 | |
| 5 | 2019 | 2 | |
| 6 | Scaling Nonparametric Bayesian Inference via Subsample-Annealing | 2014 | 1 |
| 7 | Automated equational reasoning in nondeterministic lambda-calculi modulo theories H * | 2009 | 1 |
| 8 | MCMC, Particle Filtering, and Programmable Hierarchical Modeling [R package nimble version 0.11.0] | 2021 | 0 |
About Fritz Obermeyer
Fritz Obermeyer is a scholar working on Artificial Intelligence, Signal Processing, Computational Theory and Mathematics, General Health Professions and Control and Systems Engineering, having authored 8 papers that have together received 34 indexed citations. Recurring topics across this work include Target Tracking and Data Fusion in Sensor Networks (3 papers), Gaussian Processes and Bayesian Inference (2 papers), Time Series Analysis and Forecasting (2 papers), Hermeneutics and Narrative Identity (1 paper), Bayesian Modeling and Causal Inference (1 paper), Logic, Reasoning, and Knowledge (1 paper), Machine Learning and Data Classification (1 paper) and Anomaly Detection Techniques and Applications (1 paper). The work is most often cited by research in Computational Mathematics (1 citation), Artificial Intelligence (24 citations), Signal Processing (5 citations), Computer Graphics and Computer-Aided Design (1 citation) and Instrumentation (1 citation). Fritz Obermeyer has collaborated with scholars based in United States and Israel. Frequent co-authors include Aubrey B. Poore, Martin Jankowiak, Scott A. Miller, Daniel Turek, Alexander M. Rush, Abel Rodríguez, Perry de Valpine, Duncan Temple Lang, Neeraj Pradhan and Christopher J. Paciorek. Their work appears in journals such as arXiv (Cornell University), Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE, International Conference on Artificial Intelligence and Statistics and International Conference on Machine Learning.
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.