Mariano Tepper

840 total citations
29 papers, 460 citations indexed

About

Mariano Tepper is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Cognitive Neuroscience. According to data from OpenAlex, Mariano Tepper has authored 29 papers receiving a total of 460 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computer Vision and Pattern Recognition, 8 papers in Artificial Intelligence and 7 papers in Cognitive Neuroscience. Recurrent topics in Mariano Tepper's work include Autism Spectrum Disorder Research (6 papers), Child Development and Digital Technology (5 papers) and Sparse and Compressive Sensing Techniques (4 papers). Mariano Tepper is often cited by papers focused on Autism Spectrum Disorder Research (6 papers), Child Development and Digital Technology (5 papers) and Sparse and Compressive Sensing Techniques (4 papers). Mariano Tepper collaborates with scholars based in United States, Argentina and Uruguay. Mariano Tepper's co-authors include Guillermo Sapiro, Géraldine Dawson, Helen L. Egger, Jordan Hashemi, Qiang Qiu, Kimberly L. H. Carpenter, Kathleen Campbell, Steven Espinosa, Nikolaos Papanikolopoulos and Julio Jacobo-Berlles and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Signal Processing and The Journal of Pediatrics.

In The Last Decade

Mariano Tepper

27 papers receiving 446 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mariano Tepper United States 11 240 109 103 66 52 29 460
Zhi Zheng United States 15 509 2.1× 186 1.7× 82 0.8× 118 1.8× 117 2.3× 31 809
Christopher Cieri United States 14 193 0.8× 70 0.6× 41 0.4× 645 9.8× 66 1.3× 61 963
Richard Leibbrandt Australia 9 126 0.5× 33 0.3× 41 0.4× 128 1.9× 9 0.2× 37 426
Anibal Sólon Heinsfeld United States 4 573 2.4× 46 0.4× 16 0.2× 71 1.1× 10 0.2× 7 681
Marlena Duda United States 11 676 2.8× 212 1.9× 12 0.1× 59 0.9× 52 1.0× 30 861
G. Muralidhar Bairy India 11 323 1.3× 14 0.1× 33 0.3× 40 0.6× 23 0.4× 32 517
Ognjen Rudovic United States 17 196 0.8× 37 0.3× 726 7.0× 217 3.3× 21 0.4× 45 1.1k
D. Xu United States 5 138 0.6× 56 0.5× 14 0.1× 72 1.1× 60 1.2× 10 382
Latika Singh India 11 132 0.6× 17 0.2× 87 0.8× 84 1.3× 15 0.3× 47 418
Agnieszka Landowska Poland 12 133 0.6× 30 0.3× 42 0.4× 73 1.1× 18 0.3× 39 350

Countries citing papers authored by Mariano Tepper

Since Specialization
Citations

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

Fields of papers citing papers by Mariano Tepper

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mariano Tepper

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

All Works

20 of 20 papers shown
1.
Mateos, Gonzalo, et al.. (2024). Block Successive Convex Approximation for Concomitant Linear DAG Estimation. 1–5. 1 indexed citations
2.
Tepper, Mariano, et al.. (2019). Strip the Stripes: Artifact Detection and Removal for Scanning Electron Microscopy Imaging. 1060–1064. 3 indexed citations
3.
Tepper, Mariano, et al.. (2019). Geometry of Shared Representations.
4.
Tepper, Mariano, Anirvan M. Sengupta, & Dmitri B. Chklovskii. (2018). Clustering is semidefinitely not that hard: Nonnegative SDP for manifold disentangling. Journal of Machine Learning Research. 19(82). 1–30. 2 indexed citations
5.
Egger, Helen L., Géraldine Dawson, Jordan Hashemi, et al.. (2018). Automatic emotion and attention analysis of young children at home: a ResearchKit autism feasibility study. npj Digital Medicine. 1(1). 20–20. 75 indexed citations
6.
Campbell, Kathleen, Kimberly L. H. Carpenter, Jordan Hashemi, et al.. (2018). Computer vision analysis captures atypical attention in toddlers with autism. Autism. 23(3). 619–628. 74 indexed citations
7.
Campbell, Kathleen, Kimberly L. H. Carpenter, Steven Espinosa, et al.. (2017). Use of a Digital Modified Checklist for Autism in Toddlers – Revised with Follow-up to Improve Quality of Screening for Autism. The Journal of Pediatrics. 183. 133–139.e1. 46 indexed citations
8.
Tepper, Mariano, Anirvan M. Sengupta, & Dmitri B. Chklovskii. (2017). The surprising secret identity of the semidefinite relaxation of K-means: manifold learning.. 1 indexed citations
9.
Tepper, Mariano & Guillermo Sapiro. (2016). Compressed Nonnegative Matrix Factorization Is Fast and Accurate. IEEE Transactions on Signal Processing. 64(9). 2269–2283. 25 indexed citations
10.
Tepper, Mariano & Guillermo Sapiro. (2016). A short-graph fourier transform via personalized pagerank vectors. 4806–4810. 8 indexed citations
11.
Tepper, Mariano, Alasdair Newson, Pablo Sprechmann, & Guillermo Sapiro. (2015). Multi-temporal foreground detection in videos. 11. 4599–4603.
12.
Newson, Alasdair, Mariano Tepper, & Guillermo Sapiro. (2015). Low-Rank Spatio-Temporal Video Segmentation. 103.1–103.12. 2 indexed citations
13.
Hashemi, Jordan, Kathleen Campbell, Kimberly L. H. Carpenter, et al.. (2015). A scalable app for measuring autism risk behaviors in young children: A technical validity and feasibility study. SHILAP Revista de lepidopterología. 11 indexed citations
14.
Tepper, Mariano, Thiago V. Spina, Amy Esler, et al.. (2014). Computer Vision Tools for Low-Cost and Noninvasive Measurement of Autism-Related Behaviors in Infants. SHILAP Revista de lepidopterología. 2014. 1–12. 51 indexed citations
15.
Tepper, Mariano & Guillermo Sapiro. (2014). A Biclustering Framework for Consensus Problems. SIAM Journal on Imaging Sciences. 7(4). 2488–2525. 7 indexed citations
16.
Tepper, Mariano, Pablo Musé, & Andrés Almansa. (2013). On the Role of Contrast and Regularity in Perceptual Boundary Saliency. Journal of Mathematical Imaging and Vision. 48(3). 396–412. 1 indexed citations
17.
Tepper, Mariano, et al.. (2013). Face recognition on partially occluded images using compressed sensing. Pattern Recognition Letters. 36. 235–242. 44 indexed citations
18.
Spina, Thiago V., Mariano Tepper, Amy Esler, et al.. (2012). A computer vision approach for the assessment of autism-related behavioral markers. 1–7. 35 indexed citations
19.
Tepper, Mariano, et al.. (2012). If you are happy and you know it... tweet. 1602–1606. 27 indexed citations
20.
Sprous, Dennis, Yingsheng Zhang, Lei Zhang, Zhaolin Wang, & Mariano Tepper. (2005). Kinase inhibitor recognition by use of a multivariable QSAR model. Journal of Molecular Graphics and Modelling. 24(4). 278–295. 10 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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