Rakshit Trivedi
- Artificial Intelligence top 5%
- Information Systems top 5%
- Statistical and Nonlinear Physics top 5%
- Transportation top 5%
- Applied Mathematics top 5%
- Co-authors
- Le SongHanjun DaiNan DuManuel Gomez-RodriguezUtkarsh UpadhyayHongyuan ZhaMehrdad FarajtabarJacob Eisenstein
- Topics
- Complex Network Analysis Techniques (4 papers)Recommender Systems and Techniques (3 papers)Advanced Graph Neural Networks (3 papers)
- Journals
- arXiv (Cornell University)North American Chapter of the Association for Computational LinguisticsNeural Information Processing Systems
- Partner nations
- United StatesChinaGermany
In The Last Decade
Rakshit Trivedi
12 papers receiving 519 citations
Hit Papers
Peers
Comparison fields: 5 of 72
- Artificial Intelligence 289
- Information Systems 129
- Statistical and Nonlinear Physics 124
- Transportation 97
- Applied Mathematics 82
Countries citing papers authored by Rakshit Trivedi
This map shows the geographic impact of Rakshit Trivedi'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 Rakshit Trivedi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rakshit Trivedi more than expected).
Fields of papers citing papers by Rakshit Trivedi
This network shows the impact of papers produced by Rakshit Trivedi. 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 Rakshit Trivedi. The network helps show where Rakshit Trivedi may publish in the future.
Co-authorship network of co-authors of Rakshit Trivedi
This figure shows the co-authorship network connecting the top 25 collaborators of Rakshit Trivedi. A scholar is included among the top collaborators of Rakshit Trivedi 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 Rakshit Trivedi. Rakshit Trivedi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 11 | |
| 2 | Learning Strategic Network Emergence Games | 1 |
| 3 | DyRep: Learning Representations over Dynamic Graphs | 126 |
| 4 | 24 | |
| 5 | Fake News Mitigation via Point Process Based Intervention | 15 |
| 6 | Deep Mean Field Games for Learning Optimal Behavior Policy of Large Populations. | 9 |
| 7 | Recurrent Coevolutionary Feature Embedding Processes for Recommendation | 5 |
| 8 | Coevolutionary Latent Feature Processes for Continuous-Time User-Item Interactions | 24 |
| 9 | Recurrent Temporal Point Process | 1 |
| 10 | Recurrent Marked Temporal Point Processesbreakdown → | 279 |
| 11 | 31 | |
| 12 | Discourse Connectors for Latent Subjectivity in Sentiment Analysis | 20 |
About Rakshit Trivedi
Rakshit Trivedi is a scholar working on Transportation, Statistical and Nonlinear Physics and Management Science and Operations Research, having authored 12 papers that have together received 546 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (4 papers), Recommender Systems and Techniques (3 papers) and Advanced Graph Neural Networks (3 papers). The work is most often cited by research in Transportation (97 citations), Statistical and Nonlinear Physics (124 citations) and Artificial Intelligence (289 citations). Rakshit Trivedi has collaborated with scholars based in United States, China and Germany. Frequent co-authors include Le Song, Hanjun Dai, Nan Du, Manuel Gomez-Rodriguez, Utkarsh Upadhyay, Hongyuan Zha, Mehrdad Farajtabar, Jacob Eisenstein, Yichen Wang and Yichen Wang. Their work appears in journals such as arXiv (Cornell University), North American Chapter of the Association for Computational Linguistics 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.