William Peebles
Impact in
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- Generative Adversarial Networks and Image Synthesis
- Advanced Vision and Imaging
- Image and Signal Denoising Methods
- Advanced Image Processing Techniques
- Advanced Neural Network Applications
- Video Analysis and Summarization
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- Computer Graphics and Visualization Techniques
Papers in
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- Generative Adversarial Networks and Image Synthesis 2
- Advanced Image and Video Retrieval Techniques 1
- Advanced Vision and Imaging 1
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- Modular Robots and Swarm Intelligence 2
- Co-authors
- Saining Xie (1 shared paper)Jun-Yan Zhu (1 shared paper)Richard Zhang (1 shared paper)Eli Shechtman (1 shared paper)Antonio Torralba (1 shared paper)Alexei A. Efros (1 shared paper)Pattie Maes (2 shared papers)Sang-won Leigh (2 shared papers)
- Journals
- 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (1 paper)
- Partner nations
- United States
In The Last Decade
William Peebles
4 papers receiving 606 citations
William Peebles's Hit Papers
Peers
Comparison fields: 5 of 85
- Computer Vision and Pattern Recognition 307
- Computer Graphics and Computer-Aided Design 52
- Signal Processing 49
- Media Technology 39
- Human-Computer Interaction 22
Countries citing papers authored by William Peebles
This map shows the geographic impact of William Peebles'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 William Peebles with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites William Peebles more than expected).
Fields of papers citing papers by William Peebles
This network shows the impact of papers produced by William Peebles. 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 William Peebles. The network helps show where William Peebles may publish in the future.
Co-authors
The 8 scholars most cited alongside William Peebles, 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 | Scalable Diffusion Models with Transformers Hit paper breakdown → | 2023 | 577 |
| 2 | 2022 | 30 | |
| 3 | 2018 | 10 | |
| 4 | 2017 | 5 |
About William Peebles
William Peebles is a scholar working on Computer Vision and Pattern Recognition, Mechanical Engineering, Biomedical Engineering, Control and Systems Engineering and Signal Processing, having authored 4 papers that have together received 622 indexed citations. Recurring topics across this work include Modular Robots and Swarm Intelligence (2 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Interactive and Immersive Displays (1 paper), Advanced Image and Video Retrieval Techniques (1 paper), Advanced Vision and Imaging (1 paper), Prosthetics and Rehabilitation Robotics (1 paper), Advanced Neuroimaging Techniques and Applications (1 paper) and Music and Audio Processing (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (307 citations), Computer Graphics and Computer-Aided Design (52 citations), Signal Processing (49 citations), Media Technology (39 citations) and Human-Computer Interaction (22 citations). William Peebles has collaborated with scholars based in United States. Frequent co-authors include Saining Xie, Jun-Yan Zhu, Richard Zhang, Eli Shechtman, Antonio Torralba, Alexei A. Efros, Pattie Maes and Sang-won Leigh. Their work appears in journals such as 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
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.