Chenlin Meng
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- Generative Adversarial Networks and Image Synthesis 5
- Advanced Neural Network Applications 2
- Advanced Image and Video Retrieval Techniques 2
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- Model Reduction and Neural Networks 3
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- Domain Adaptation and Few-Shot Learning 2
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- Sustainable Development and Environmental Policy 1
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- Sparse and Compressive Sensing Techniques 1
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- Automated Road and Building Extraction 1
- Co-authors
- Stefano ErmonJonathan HoTim SalimansRuiqi GaoDiederik P. KingmaRobin RombachJiaming SongAbhishek Sinha
- Cited by
- Computer Vision and Pattern RecognitionComputer Graphics and Computer-Aided DesignMedia Technology
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)IEEE Expert (1 paper)arXiv (Cornell University) (2 papers)
- Partner nations
- United StatesBelgiumCanada
In The Last Decade
Chenlin Meng
14 papers receiving 199 citations
Hit Papers
Peers
Comparison fields: 5 of 71
- Computer Vision and Pattern Recognition 120
- Computer Graphics and Computer-Aided Design 18
- Media Technology 20
- Statistical and Nonlinear Physics 22
- Computational Mathematics 1
Countries citing papers authored by Chenlin Meng
This map shows the geographic impact of Chenlin Meng'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 Chenlin Meng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chenlin Meng more than expected).
Fields of papers citing papers by Chenlin Meng
This network shows the impact of papers produced by Chenlin Meng. 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 Chenlin Meng. The network helps show where Chenlin Meng may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Chenlin Meng, 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 | 2025 | 2 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2025 | 0 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 1 | |
| 7 | 2024 | 2 | |
| 8 | 2024 | 3 | |
| 9 | On Distillation of Guided Diffusion Modelsbreakdown → | 2023 | 117 |
| 10 | 2023 | 12 | |
| 11 | 2022 | 11 | |
| 12 | D2C: Diffusion-Decoding Models for Few-Shot Conditional Generation | 2021 | 32 |
| 13 | 2021 | 2 | |
| 14 | 2021 | 4 | |
| 15 | Nonlinear Equation Solving: A Faster Alternative to Feedforward Computation | 2020 | 1 |
| 16 | 2019 | 14 | |
| 17 | 1991 | 8 |
About Chenlin Meng
Chenlin Meng is a scholar working on Computer Vision and Pattern Recognition, Software and Artificial Intelligence, having authored 17 papers that have together received 210 indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (5 papers), Model Reduction and Neural Networks (3 papers), Advanced Neural Network Applications (2 papers), Advanced Image and Video Retrieval Techniques (2 papers), Domain Adaptation and Few-Shot Learning (2 papers), Sustainable Development and Environmental Policy (1 paper), Sparse and Compressive Sensing Techniques (1 paper) and Automated Road and Building Extraction (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (120 citations), Computer Graphics and Computer-Aided Design (18 citations) and Media Technology (20 citations). Chenlin Meng has collaborated with scholars based in United States, Belgium and Canada. Frequent co-authors include Stefano Ermon, Jonathan Ho, Tim Salimans, Ruiqi Gao, Diederik P. Kingma, Robin Rombach, Jiaming Song, Abhishek Sinha, Marshall Burke and David B. Lobell. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Expert, arXiv (Cornell University), Proceedings of the AAAI Conference on Artificial Intelligence and Neural Information Processing Systems.
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.