Anand Louis
- Artificial Intelligence top 10%
- Computational Theory and Mathematics top 10%
- Statistical and Nonlinear Physics top 10%
- Computer Vision and Pattern Recognition
- Molecular Biology
- Co-authors
- Madhav NimishakaviNaganand YadatiPrateek YadavPartha TalukdarVikram NitinSantosh VempalaT-H. Hubert ChanChenzi Zhang
- Topics
- Complexity and Algorithms in Graphs (6 papers)Advanced Graph Theory Research (3 papers)Complex Network Analysis Techniques (3 papers)
- Cited by
- Computational MathematicsStatistical and Nonlinear PhysicsComputational Theory and Mathematics
- Partner nations
- United StatesIndiaUnited Kingdom
In The Last Decade
Anand Louis
14 papers receiving 193 citations
Peers
Comparison fields: 5 of 43
- Artificial Intelligence 97
- Computational Theory and Mathematics 66
- Statistical and Nonlinear Physics 64
- Computer Vision and Pattern Recognition 37
- Molecular Biology 28
Countries citing papers authored by Anand Louis
This map shows the geographic impact of Anand Louis'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 Anand Louis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anand Louis more than expected).
Fields of papers citing papers by Anand Louis
This network shows the impact of papers produced by Anand Louis. 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 Anand Louis. The network helps show where Anand Louis may publish in the future.
Co-authorship network of co-authors of Anand Louis
This figure shows the co-authorship network connecting the top 25 collaborators of Anand Louis. A scholar is included among the top collaborators of Anand Louis 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 Anand Louis. Anand Louis 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 | Ranking for Individual and Group Fairness Simultaneously. | 1 |
| 3 | 49 | |
| 4 | HyperGCN: A New Method For Training Graph Convolutional Networks on Hypergraphs | 26 |
| 5 | HyperGCN: Hypergraph Convolutional Networks for Semi-Supervised Classification. | 12 |
| 6 | 1 | |
| 7 | Link Prediction in Hypergraphs using Graph Convolutional Networks | 6 |
| 8 | 32 | |
| 9 | 4 | |
| 10 | 5 | |
| 11 | 21 | |
| 12 | 2 | |
| 13 | 18 | |
| 14 | 3 | |
| 15 | 17 |
About Anand Louis
Anand Louis is a scholar working on Computational Mathematics, Computational Theory and Mathematics and Computer Graphics and Computer-Aided Design, having authored 15 papers that have together received 197 indexed citations. Recurring topics across this work include Complexity and Algorithms in Graphs (6 papers), Advanced Graph Theory Research (3 papers) and Complex Network Analysis Techniques (3 papers). The work is most often cited by research in Computational Mathematics (15 citations), Statistical and Nonlinear Physics (64 citations) and Computational Theory and Mathematics (66 citations). Anand Louis has collaborated with scholars based in United States, India and United Kingdom. Frequent co-authors include Madhav Nimishakavi, Naganand Yadati, Prateek Yadav, Partha Talukdar, Vikram Nitin, Santosh Vempala, T-H. Hubert Chan, Chenzi Zhang, Zhihao Gavin Tang and Prasad Raghavendra. Their work appears in journals such as Journal of the ACM, Mathematical Programming and Theory of Computing.
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.