Dietmar Ebner

2.1k citations
12 papers · 1.2k · 2 hit papers · h-index 7

Impact in

Papers in

Dietmar Ebner

11 papers receiving 1.0k citations

Dietmar Ebner's Hit Papers

Hidden technical debt in Machine learning systems 2015 · 457 citations
4570+4+8Years since publication100200300400500

Peers

Dietmar Ebner
Comparison fields: 5 of 107
  • Health Informatics 35
  • Information Systems 420
  • Artificial Intelligence 531
  • Management Science and Operations Research 186
  • Information Systems and Management 97
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Todd Phillips United States
Mohsen Kahani Iran
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Gillian Dobbie New Zealand
Farid Meziane United Kingdom
Freddy Lécué United Kingdom
Ahmet Soylu Norway
Aditya Parameswaran United States
Fuyuki Ishikawa Japan
Alessandro Ricci Italy
Dietmar Ebner relative to Todd Phillips United States Todd Phillips's profile →
Citations per field
00.5×1.5×
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Citations per year

Countries citing papers authored by Dietmar Ebner

Since Specialization
Citations

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

Fields of papers citing papers by Dietmar Ebner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Dietmar Ebner, 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 Dietmar Ebner Line = papers co-authored together Dietmar Ebner links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1
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Hit paper breakdown →
2013511
2
Hidden technical debt in Machine learning systems
Hit paper breakdown →
2015457
3
Machine Learning: The High Interest Credit Card of Technical Debt
2014126
4 200718
5 201117
6 200814
7 200710
8 20094
9 20083
10 20072
11 20101
12 20130

About Dietmar Ebner

Dietmar Ebner is a scholar working on Hardware and Architecture, Computer Networks and Communications, Information Systems and Management, Artificial Intelligence and Information Systems, having authored 12 papers that have together received 1.2k indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (8 papers), Scientific Computing and Data Management (5 papers), Software Testing and Debugging Techniques (3 papers), Distributed and Parallel Computing Systems (3 papers), Logic, programming, and type systems (3 papers), Embedded Systems Design Techniques (2 papers), Advanced Data Storage Technologies (2 papers) and Software Engineering Research (2 papers). The work is most often cited by research in Health Informatics (35 citations), Information Systems (420 citations), Artificial Intelligence (531 citations), Management Science and Operations Research (186 citations) and Information Systems and Management (97 citations). Dietmar Ebner has collaborated with scholars based in Austria, United States and Australia. Frequent co-authors include Todd Phillips, Eugene Davydov, Gary D. Holt, D. Sculley, Daniel Golovin, Michael Young, H. Brendan McMahan, Lan Nie, Sharat Chikkerur and Martin Wattenberg. Their work appears in journals such as ACM SIGPLAN Notices, The International Journal of High Performance Computing Applications, Discrete Optimization, Neural Information Processing Systems and OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information).

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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