John Paisley
- Computer Vision and Pattern Recognition top 0.1%
- Media Technology top 0.1%
- Artificial Intelligence top 0.5%
- Computational Mechanics top 2%
- Signal Processing top 1%
- Co-authors
- Xinghao DingXueyang FuYue HuangDavid M. BleiJia‐Bin HuangLawrence CarinDelu ZengYinghao Liao
- Topics
- Bayesian Methods and Mixture Models (24 papers)Sparse and Compressive Sensing Techniques (19 papers)Image and Signal Denoising Methods (15 papers)
- Journals
- JAMASHILAP Revista de lepidopterologíaIEEE Transactions on Pattern Analysis and Machine Intelligence
- Partner nations
- United StatesChinaAustralia
In The Last Decade
John Paisley
102 papers receiving 6.7k citations
Hit Papers
Peers
Comparison fields: 5 of 185
- Computer Vision and Pattern Recognition 3.9k
- Media Technology 2.0k
- Artificial Intelligence 1.7k
- Computational Mechanics 558
- Signal Processing 491
Countries citing papers authored by John Paisley
This map shows the geographic impact of John Paisley'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 John Paisley with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Paisley more than expected).
Fields of papers citing papers by John Paisley
This network shows the impact of papers produced by John Paisley. 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 John Paisley. The network helps show where John Paisley may publish in the future.
Co-authorship network of co-authors of John Paisley
This figure shows the co-authorship network connecting the top 25 collaborators of John Paisley. A scholar is included among the top collaborators of John Paisley 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 John Paisley. John Paisley is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 0 | |
| 4 | 25 | |
| 5 | A state-space model for inferring effective connectivity of latent neural dynamics from simultaneous EEG/fMRI | 4 |
| 6 | 82 | |
| 7 | 3 | |
| 8 | CRVI: Convex Relaxation for Variational Inference | 3 |
| 9 | Deep Bayesian Nonparametric Tracking. | 5 |
| 10 | Removing Rain from Single Images via a Deep Detail Networkbreakdown → | 796 |
| 11 | Markov latent feature models | 1 |
| 12 | Stochastic Variational Inference for the HDP-HMM. | 5 |
| 13 | Markov Mixed Membership Models | 5 |
| 14 | Landmarking Manifolds with Gaussian Processes | 4 |
| 15 | Stochastic variational inferencebreakdown → | 669 |
| 16 | Stick-Breaking Beta Processes and the Poisson Process | 13 |
| 17 | Online Variational Inference for the Hierarchical Dirichlet Process | 194 |
| 18 | Non-Parametric Bayesian Dictionary Learning for Sparse Image Representations | 147 |
| 19 | 18 | |
| 20 | 22 |
About John Paisley
John Paisley is a scholar working on Statistics and Probability, Computational Mathematics and Signal Processing, having authored 108 papers that have together received 6.9k indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (24 papers), Sparse and Compressive Sensing Techniques (19 papers) and Image and Signal Denoising Methods (15 papers). The work is most often cited by research in Media Technology (2.0k citations), Computer Vision and Pattern Recognition (3.9k citations) and Computational Mathematics (49 citations). John Paisley has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Xinghao Ding, Xueyang Fu, Yue Huang, David M. Blei, Jia‐Bin Huang, Lawrence Carin, Delu Zeng, Yinghao Liao, Matthew D. Hoffman and Chong Wang. Their work appears in journals such as JAMA, SHILAP Revista de lepidopterología and IEEE Transactions on Pattern Analysis and Machine Intelligence.
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.