Jaan Altosaar

1.1k total citations
13 papers, 251 citations indexed

About

Jaan Altosaar is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Jaan Altosaar has authored 13 papers receiving a total of 251 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 2 papers in Information Systems. Recurrent topics in Jaan Altosaar's work include Topic Modeling (3 papers), Speech and Audio Processing (2 papers) and Music and Audio Processing (2 papers). Jaan Altosaar is often cited by papers focused on Topic Modeling (3 papers), Speech and Audio Processing (2 papers) and Music and Audio Processing (2 papers). Jaan Altosaar collaborates with scholars based in United States, Canada and Sweden. Jaan Altosaar's co-authors include David M. Blei, Laurent Charlin, Dawen Liang, Tony T. Wong, Charles A. Popkin, Diego Jaramillo, John R. Zech, P. Henelius, Zhanyang Hao and Jeffrey G. Rau and has published in prestigious journals such as Physical review. B., Pediatric Radiology and Stat.

In The Last Decade

Jaan Altosaar

13 papers receiving 249 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jaan Altosaar United States 5 145 110 48 36 32 13 251
Jiaqing Liang China 12 64 0.4× 233 2.1× 30 0.6× 4 0.1× 51 1.6× 57 337
Paolo Puliti Italy 9 46 0.3× 82 0.7× 22 0.5× 19 0.5× 7 0.2× 32 241
Cheng-Fa Tsai Taiwan 8 31 0.2× 80 0.7× 82 1.7× 8 0.2× 6 0.2× 19 208
Dong‐Gi Lee South Korea 10 15 0.1× 38 0.3× 42 0.9× 26 0.7× 2 0.1× 33 252
Zihan Wang China 9 30 0.2× 198 1.8× 33 0.7× 4 0.1× 21 0.7× 40 278
Anuradha India 9 27 0.2× 50 0.5× 13 0.3× 5 0.1× 7 0.2× 42 277
Shuai Zhao China 10 18 0.1× 153 1.4× 37 0.8× 6 0.2× 9 0.3× 41 246
Mohammad Rezwanul Huq Bangladesh 8 100 0.7× 82 0.7× 17 0.4× 4 0.1× 15 0.5× 36 289

Countries citing papers authored by Jaan Altosaar

Since Specialization
Citations

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

Fields of papers citing papers by Jaan Altosaar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jaan Altosaar

This figure shows the co-authorship network connecting the top 25 collaborators of Jaan Altosaar. A scholar is included among the top collaborators of Jaan Altosaar 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 Jaan Altosaar. Jaan Altosaar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

13 of 13 papers shown
1.
Zech, John R., Diego Jaramillo, Jaan Altosaar, Charles A. Popkin, & Tony T. Wong. (2023). Artificial intelligence to identify fractures on pediatric and young adult upper extremity radiographs. Pediatric Radiology. 53(12). 2386–2397. 24 indexed citations
2.
Nieva, Harry Reyes, Tony Sun, Jaan Altosaar, et al.. (2023). Auditing Learned Associations in Deep Learning Approaches to Extract Race and Ethnicity from Clinical Text.. PubMed. 2023. 289–298. 1 indexed citations
3.
Sun, Tony, Shreyas Bhave, Jaan Altosaar, & Noémie Elhadad. (2022). Assessing Phenotype Definitions for Algorithmic Fairness.. PubMed. 2022. 1032–1041. 6 indexed citations
4.
Altosaar, Jaan, Rajesh Ranganath, & Wesley Tansey. (2021). RankFromSets: Scalable set recommendation with optimal recall. Stat. 10(1). 4 indexed citations
5.
Altosaar, Jaan, et al.. (2020). Recommending Interesting Writing using a Controllable, Explanation-Aware Visual Interface.. Conference on Recommender Systems. 77–80. 2 indexed citations
6.
Altosaar, Jaan. (2020). Probabilistic Modeling of Structure in Science: Statistical Physics to Recommender Systems. 1 indexed citations
7.
Dieng, Adji Bousso, Rajesh Ranganath, Jaan Altosaar, & David M. Blei. (2018). Noisin: Unbiased Regularization for Recurrent Neural Networks. International Conference on Machine Learning. 1252–1261. 1 indexed citations
8.
Ranganath, Rajesh, Jaan Altosaar, Dustin Tran, & David M. Blei. (2016). Operator variational inference. Neural Information Processing Systems. 29. 496–504. 3 indexed citations
9.
Liang, Dawen, Jaan Altosaar, Laurent Charlin, & David M. Blei. (2016). Factorization Meets the Item Embedding. 59–66. 162 indexed citations
10.
Henelius, P., Matthew Enjalran, Zhanyang Hao, et al.. (2016). Refrustration and competing orders in the prototypicalDy2Ti2O7spin ice material. Physical review. B.. 93(2). 36 indexed citations
11.
Altosaar, Jaan. (2016). Tutorial - What is a Variational Autoencoder?. Zenodo (CERN European Organization for Nuclear Research). 5 indexed citations
12.
Altosaar, Jaan, et al.. (2015). MusicMapper: Interactive 2D Representations of Music Samples for In-Browser Remixing and Exploration. New Interfaces for Musical Expression. 325–326. 2 indexed citations
13.
Altosaar, Jaan, et al.. (2015). Sonification Of Fish Movement Using Pitch Mesh Pairs. Zenodo (CERN European Organization for Nuclear Research). 4 indexed citations

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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