Amarnag Subramanya
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 5%
- Signal Processing top 5%
- Management Science and Operations Research top 5%
- Information Systems top 10%
- Co-authors
- Jeff BilmesFernando PereiraPartha TalukdarAndrew McCallumSameer SinghSlav PetrovDan GillickCliff Brunk
- Topics
- Topic Modeling (9 papers)Speech Recognition and Synthesis (9 papers)Speech and Audio Processing (8 papers)
- Partner nations
- United StatesIndiaTaiwan
In The Last Decade
Amarnag Subramanya
30 papers receiving 825 citations
Peers
Comparison fields: 5 of 81
- Artificial Intelligence 713
- Computer Vision and Pattern Recognition 218
- Signal Processing 159
- Management Science and Operations Research 100
- Information Systems 57
Countries citing papers authored by Amarnag Subramanya
This map shows the geographic impact of Amarnag Subramanya'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 Amarnag Subramanya with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Amarnag Subramanya more than expected).
Fields of papers citing papers by Amarnag Subramanya
This network shows the impact of papers produced by Amarnag Subramanya. 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 Amarnag Subramanya. The network helps show where Amarnag Subramanya may publish in the future.
Co-authorship network of co-authors of Amarnag Subramanya
This figure shows the co-authorship network connecting the top 25 collaborators of Amarnag Subramanya. A scholar is included among the top collaborators of Amarnag Subramanya 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 Amarnag Subramanya. Amarnag Subramanya is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 18 | |
| 2 | 64 | |
| 3 | 112 | |
| 4 | 37 | |
| 5 | Wikilinks: A Large-scale Cross-Document Coreference Corpus Labeled via Links to Wikipedia | 52 |
| 6 | Semi-Supervised Learning with Measure Propagation | 60 |
| 7 | Large-Scale Cross-Document Coreference Using Distributed Inference and Hierarchical Models | 81 |
| 8 | Efficient Graph-Based Semi-Supervised Learning of Structured Tagging Models | 84 |
| 9 | Entropic Graph Regularization in Non-Parametric Semi-Supervised Classification | 43 |
| 10 | A Semi-Supervised Learning Algorithm for Multi-Layered Perceptrons | 2 |
| 11 | 11 | |
| 12 | 40 | |
| 13 | 2 | |
| 14 | 20 | |
| 15 | 12 | |
| 16 | 5 | |
| 17 | 2 | |
| 18 | 10 | |
| 19 | 2 | |
| 20 | 1 |
About Amarnag Subramanya
Amarnag Subramanya is a scholar working on Signal Processing, Artificial Intelligence and Human-Computer Interaction, having authored 30 papers that have together received 907 indexed citations. Recurring topics across this work include Topic Modeling (9 papers), Speech Recognition and Synthesis (9 papers) and Speech and Audio Processing (8 papers). The work is most often cited by research in Artificial Intelligence (713 citations), Signal Processing (159 citations) and Computer Vision and Pattern Recognition (218 citations). Amarnag Subramanya has collaborated with scholars based in United States, India and Taiwan. Frequent co-authors include Jeff Bilmes, Fernando Pereira, Partha Talukdar, Andrew McCallum, Sameer Singh, Slav Petrov, Dan Gillick, Cliff Brunk, Oriol Vinyals and Nevena Lazic. Their work appears in journals such as Journal of Machine Learning Research, IEEE Signal Processing Letters and Speech Communication.
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.