Yee Whye Teh
- Artificial Intelligence top 0.1%
- Computer Vision and Pattern Recognition top 0.5%
- Statistics and Probability top 0.5%
- Signal Processing top 1%
- Molecular Biology
- Co-authors
- Michael I. JordanDavid M. BleiMatthew J. BealMax WellingZoubin GhahramaniAndriy MnihDilan GörürJurgen Van Gael
- Topics
- Bayesian Methods and Mixture Models (51 papers)Gaussian Processes and Bayesian Inference (22 papers)Algorithms and Data Compression (14 papers)
- Partner nations
- United KingdomUnited StatesItaly
In The Last Decade
Yee Whye Teh
119 papers receiving 6.6k citations
Hit Papers
Peers
Comparison fields: 5 of 176
- Artificial Intelligence 4.7k
- Computer Vision and Pattern Recognition 1.2k
- Statistics and Probability 987
- Signal Processing 752
- Molecular Biology 579
Countries citing papers authored by Yee Whye Teh
This map shows the geographic impact of Yee Whye Teh'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 Yee Whye Teh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yee Whye Teh more than expected).
Fields of papers citing papers by Yee Whye Teh
This network shows the impact of papers produced by Yee Whye Teh. 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 Yee Whye Teh. The network helps show where Yee Whye Teh may publish in the future.
Co-authorship network of co-authors of Yee Whye Teh
This figure shows the co-authorship network connecting the top 25 collaborators of Yee Whye Teh. A scholar is included among the top collaborators of Yee Whye Teh 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 Yee Whye Teh. Yee Whye Teh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Inferring the effectiveness of government interventions against COVID-19breakdown → | 630 |
| 2 | Bayesian Deep Ensembles via the Neural Tangent Kernel | 1 |
| 3 | Variational Estimators for Bayesian Optimal Experimental Design. | 0 |
| 4 | Scaling up the Automatic Statistician: Scalable Structure Discovery using Gaussian Processes | 6 |
| 5 | An Analysis of Categorical Distributional Reinforcement Learning | 4 |
| 6 | 16 | |
| 7 | Relativistic Monte Carlo | 5 |
| 8 | DR-ABC: approximate Bayesian computation with kernel-based distribution regression | 5 |
| 9 | Scalable Structure Discovery in Regression using Gaussian Processes | 1 |
| 10 | Expectation particle Belief Propagation | 1 |
| 11 | Searching for objects driven by context | 31 |
| 12 | Scalable imputation of genetic data with a discrete fragmentation-coagulation process | 7 |
| 13 | Gaussian process modulated renewal processes | 17 |
| 14 | Spatial Normalized Gamma Processes | 29 |
| 15 | Dependent Dirichlet Process Spike Sorting | 21 |
| 16 | Improving Word Sense Disambiguation Using Topic Features | 25 |
| 17 | Cooled and Relaxed Survey Propagation for MRFs | 2 |
| 18 | On Improving the Efficiency of the Iterative Proportional Fitting Procedure | 15 |
| 19 | Rate-coded Restricted Boltzmann Machines for Face Recognition | 90 |
| 20 | Learning to Parse Images | 27 |
About Yee Whye Teh
Yee Whye Teh is a scholar working on Statistics and Probability, Artificial Intelligence and Signal Processing, having authored 124 papers that have together received 7.0k indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (51 papers), Gaussian Processes and Bayesian Inference (22 papers) and Algorithms and Data Compression (14 papers). The work is most often cited by research in Artificial Intelligence (4.7k citations), Statistics and Probability (987 citations) and Modeling and Simulation (466 citations). Yee Whye Teh has collaborated with scholars based in United Kingdom, United States and Italy. Frequent co-authors include Michael I. Jordan, David M. Blei, Matthew J. Beal, Max Welling, Zoubin Ghahramani, Andriy Mnih, Dilan Görür, Jurgen Van Gael, Arthur Asuncion and Padhraic Smyth. Their work appears in journals such as Science, Journal of the American Statistical Association and Nature Methods.
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.