Animashree Anandkumar

5.6k citations
106 papers · 1.8k · 1 hit paper · h-index 21

Impact in

Papers in

Animashree Anandkumar

100 papers receiving 1.7k citations

Animashree Anandkumar's Hit Papers

Tensor decompositions for learning latent variable models 2014 · 394 citations
3940+4+8Years since publication100200300

Peers

Animashree Anandkumar
Comparison fields: 5 of 129
  • Computational Mathematics 337
  • Health Informatics 64
  • Artificial Intelligence 753
  • Statistics and Probability 171
  • Computer Networks and Communications 434
Replace Anand D. Sarwate with:
Anand D. Sarwate United States
Prateek Jain India
Martin Jaggi Switzerland
Aarti Singh United States
Praneeth Netrapalli United States
Shiqian Ma United States
Alex Olshevsky United States
Antonio G. Marqués Spain
Jeff M. Phillips United States
Vincent Y. F. Tan Singapore
Animashree Anandkumar relative to Anand D. Sarwate United States Anand D. Sarwate's profile →
Citations per field
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Citations per year

Countries citing papers authored by Animashree Anandkumar

Since Specialization
Citations

This map shows the geographic impact of Animashree Anandkumar'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 Animashree Anandkumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Animashree Anandkumar more than expected).

Fields of papers citing papers by Animashree Anandkumar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Animashree Anandkumar. 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 Animashree Anandkumar. The network helps show where Animashree Anandkumar may publish in the future.

Co-authors

The 25 scholars most cited alongside Animashree Anandkumar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Animashree Anandkumar Line = papers co-authored together Animashree Anandkumar links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 106 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Tensor decompositions for learning latent variable models
Hit paper breakdown →
2014394
2 2010109
3 202385
4 201466
5 201455
6 200751
7
A Tensor Spectral Approach to Learning Mixed Membership Community Models
201349
8 202346
9 201245
10 201840
11 201137
12 202333
13
Learning Sparsely Used Overcomplete Dictionaries
201433
14 200932
15
Learning Linear Bayesian Networks with Latent Variables
201232
16 201131
17 201028
18 201125
19 201222
20
Deep Active Learning for Named Entity Recognition.
201821

About Animashree Anandkumar

Animashree Anandkumar is a scholar working on Artificial Intelligence, Computer Networks and Communications, Computational Mathematics, Computer Vision and Pattern Recognition and Statistics and Probability, having authored 106 papers that have together received 1.8k indexed citations. Recurring topics across this work include Tensor decomposition and applications (14 papers), Machine Learning and Algorithms (14 papers), Distributed Sensor Networks and Detection Algorithms (14 papers), Bayesian Modeling and Causal Inference (13 papers), Target Tracking and Data Fusion in Sensor Networks (12 papers), Statistical Methods and Inference (8 papers), Sparse and Compressive Sensing Techniques (7 papers) and Complex Network Analysis Techniques (7 papers). The work is most often cited by research in Computational Mathematics (337 citations), Health Informatics (64 citations), Artificial Intelligence (753 citations), Statistics and Probability (171 citations) and Computer Networks and Communications (434 citations). Animashree Anandkumar has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Rong Ge, Daniel Hsu, Sham M. Kakade, Matus Telgarsky, Lang Tong, Alan S. Willsky, Vincent Y. F. Tan, Ao Tang, Praneeth Netrapalli and Andrew J. Hung. Their work appears in journals such as Journal of Machine Learning Research, IEEE Transactions on Signal Processing, IEEE Transactions on Information Theory, ACM SIGMETRICS Performance Evaluation Review and The Annals of Statistics.

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.

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