Haonan Yu
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 5%
- Biomedical Engineering
- Signal Processing
- Molecular Biology
- Co-authors
- Yi YangJiang WangWei XuZhiheng HuangJeffrey Mark SiskindAndrei BarbuN. SiddharthYuewei Lin
- Topics
- Multimodal Machine Learning Applications (9 papers)Human Pose and Action Recognition (7 papers)Natural Language Processing Techniques (5 papers)
- Partner nations
- United StatesChinaIsrael
In The Last Decade
Haonan Yu
22 papers receiving 717 citations
Hit Papers
Peers
Comparison fields: 5 of 94
- Computer Vision and Pattern Recognition 578
- Artificial Intelligence 274
- Biomedical Engineering 33
- Signal Processing 30
- Molecular Biology 26
Countries citing papers authored by Haonan Yu
This map shows the geographic impact of Haonan Yu'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 Haonan Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Haonan Yu more than expected).
Fields of papers citing papers by Haonan Yu
This network shows the impact of papers produced by Haonan Yu. 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 Haonan Yu. The network helps show where Haonan Yu may publish in the future.
Co-authorship network of co-authors of Haonan Yu
This figure shows the co-authorship network connecting the top 25 collaborators of Haonan Yu. A scholar is included among the top collaborators of Haonan Yu 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 Haonan Yu. Haonan Yu 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 | 1 | |
| 3 | 1 | |
| 4 | 4 | |
| 5 | 60 | |
| 6 | 27 | |
| 7 | 14 | |
| 8 | Playing the lottery with rewards and multiple languages: lottery tickets in RL and NLP | 12 |
| 9 | 2 | |
| 10 | One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers | 17 |
| 11 | EPNAS: Efficient Progressive Neural Architecture Search | 1 |
| 12 | Guided Feature Transformation (GFT): A Neural Language Grounding Module for Embodied Agents | 1 |
| 13 | 9 | |
| 14 | 3 | |
| 15 | Video Paragraph Captioning Using Hierarchical Recurrent Neural Networksbreakdown → | 337 |
| 16 | 1 | |
| 17 | 19 | |
| 18 | 6 | |
| 19 | Grounded Language Learning from Video Described with Sentences | 62 |
| 20 | 125 |
About Haonan Yu
Haonan Yu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Geology, having authored 23 papers that have together received 746 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (9 papers), Human Pose and Action Recognition (7 papers) and Natural Language Processing Techniques (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (578 citations), Artificial Intelligence (274 citations) and Computational Mathematics (5 citations). Haonan Yu has collaborated with scholars based in United States, China and Israel. Frequent co-authors include Yi Yang, Jiang Wang, Wei Xu, Zhiheng Huang, Jeffrey Mark Siskind, Andrei Barbu, N. Siddharth, Yuewei Lin, Sven Dickinson and Song Wang. Their work appears in journals such as Journal of Climate, Carbohydrate Polymers and Advanced Science.
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.