Andrew Slavin Ross

2.7k citations
16 papers · 584 indexed · 1 hit paper · h-index 10
Topics
Explainable Artificial Intelligence (XAI) (2 papers)Advanced Database Systems and Queries (2 papers)Adversarial Robustness in Machine Learning (2 papers)
Journals
SHILAP Revista de lepidopterologíaJournal of Geophysical Research AtmospheresPLoS ONE

In The Last Decade

Andrew Slavin Ross

15 papers receiving 568 citations

Hit Papers

Improving the Adversarial Robustness and Interpretability...2018202620202023201850100150200250

Peers

Andrew Slavin Ross
Comparison fields: 5 of 98
  • Artificial Intelligence 377
  • Computer Vision and Pattern Recognition 91
  • Signal Processing 91
  • Molecular Biology 72
  • Computer Networks and Communications 57
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Citations per field
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Citations per year

Countries citing papers authored by Andrew Slavin Ross

Since Specialization
Citations

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

Fields of papers citing papers by Andrew Slavin Ross

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andrew Slavin Ross. 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 Andrew Slavin Ross. The network helps show where Andrew Slavin Ross may publish in the future.

Co-authorship network of co-authors of Andrew Slavin Ross

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

All Works

16 of 16 papers shown
#WorkIndexed citations
1 1
2 18
3 31
4 14
5 0
6
Design Continuums and the Path Toward Self-Designing Key-Value Stores that Know and Learn.
31
7 2
8 8
9
Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing Their Input Gradientsbreakdown →
282
10 2
11
Improving Sepsis Treatment Strategies by Combining Deep and Kernel-Based Reinforcement Learning.
23
12 98
13 12
14 46
15 15
16
Thrombolytic therapy: medical panel discussion
1

About Andrew Slavin Ross

Andrew Slavin Ross is a scholar working on Internal Medicine, Applied Psychology and Critical Care and Intensive Care Medicine, having authored 16 papers that have together received 584 indexed citations. Recurring topics across this work include Explainable Artificial Intelligence (XAI) (2 papers), Advanced Database Systems and Queries (2 papers) and Adversarial Robustness in Machine Learning (2 papers). The work is most often cited by research in Artificial Intelligence (377 citations), Signal Processing (91 citations) and Health Informatics (10 citations). Andrew Slavin Ross has collaborated with scholars based in United States, United Kingdom and Australia. Frequent co-authors include Finale Doshi‐Velez, Laure Zanna, Carlos Fernandez‐Granda, Ziwei Li, B. A. Brooks, Eric Sandvol, J. C. Bertrand, Dominique Page, C. Venet and Fabrice Zéni. Their work appears in journals such as SHILAP Revista de lepidopterología, Journal of Geophysical Research Atmospheres and PLoS ONE.

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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