Prateek Yadav
- Artificial Intelligence top 10%
- Electrical and Electronic Engineering
- Computer Vision and Pattern Recognition
- Statistical and Nonlinear Physics top 10%
- Computer Networks and Communications
- Co-authors
- Partha TalukdarNaganand YadatiMadhav NimishakaviAnand LouisVikram NitinYogendra Kumar PrajapatiMohit BansalSubrat Kar
- Topics
- Topic Modeling (6 papers)Advanced Graph Neural Networks (5 papers)Optical Wireless Communication Technologies (4 papers)
- Partner nations
- IndiaUnited States
In The Last Decade
Prateek Yadav
25 papers receiving 214 citations
Peers
Comparison fields: 5 of 47
- Artificial Intelligence 122
- Electrical and Electronic Engineering 51
- Computer Vision and Pattern Recognition 50
- Statistical and Nonlinear Physics 46
- Computer Networks and Communications 34
Countries citing papers authored by Prateek Yadav
This map shows the geographic impact of Prateek Yadav'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 Prateek Yadav with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Prateek Yadav more than expected).
Fields of papers citing papers by Prateek Yadav
This network shows the impact of papers produced by Prateek Yadav. 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 Prateek Yadav. The network helps show where Prateek Yadav may publish in the future.
Co-authorship network of co-authors of Prateek Yadav
This figure shows the co-authorship network connecting the top 25 collaborators of Prateek Yadav. A scholar is included among the top collaborators of Prateek Yadav 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 Prateek Yadav. Prateek Yadav 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 | 10 | |
| 4 | 7 | |
| 5 | 1 | |
| 6 | 3 | |
| 7 | 7 | |
| 8 | 2 | |
| 9 | 11 | |
| 10 | 2 | |
| 11 | 3 | |
| 12 | 12 | |
| 13 | 49 | |
| 14 | HyperGCN: A New Method For Training Graph Convolutional Networks on Hypergraphs | 26 |
| 15 | 2 | |
| 16 | Graph Convolutional Networks based Word Embeddings. | 3 |
| 17 | HyperGCN: Hypergraph Convolutional Networks for Semi-Supervised Classification. | 12 |
| 18 | Link Prediction in Hypergraphs using Graph Convolutional Networks | 6 |
| 19 | 5 | |
| 20 | 12 |
About Prateek Yadav
Prateek Yadav is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics and Computer Vision and Pattern Recognition, having authored 26 papers that have together received 220 indexed citations. Recurring topics across this work include Topic Modeling (6 papers), Advanced Graph Neural Networks (5 papers) and Optical Wireless Communication Technologies (4 papers). The work is most often cited by research in Computational Mathematics (3 citations), Artificial Intelligence (122 citations) and Statistical and Nonlinear Physics (46 citations). Prateek Yadav has collaborated with scholars based in India and United States. Frequent co-authors include Partha Talukdar, Naganand Yadati, Madhav Nimishakavi, Anand Louis, Vikram Nitin, Yogendra Kumar Prajapati, Mohit Bansal, Subrat Kar, Swarnadeep Saha and Shikhar Vashishth. Their work appears in journals such as IEEE Internet of Things Journal, Optical Engineering and Energy Reports.
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.