Jonathan Tepper

21 papers receiving 192 citations

Peers

Jonathan Tepper
Comparison fields: 5 of 76
  • General Economics, Econometrics and Finance 31
  • Management Science and Operations Research 42
  • Artificial Intelligence 70
  • Economics and Econometrics 52
  • Signal Processing 20
Replace Mohammad Ghaderi with:
Mohammad Ghaderi Spain
Jiayi Chen China
Johannes M. Lehner Austria
Youngki Shin Canada
Vitalik Buterin United States
Andrew Blake United Kingdom
Francisco Andrade Portugal
Ronald S. King United States
Andrew Y. Chen United States
Jonathan Tepper relative to Mohammad Ghaderi Spain Mohammad Ghaderi's profile →
Citations per field
00.5×3.1×
Mohammad Ghaderi · 1×
Citations per year

Countries citing papers authored by Jonathan Tepper

Since Specialization
Citations

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

Fields of papers citing papers by Jonathan Tepper

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 20 scholars most cited alongside Jonathan Tepper, 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 Jonathan Tepper Line = papers co-authored together Jonathan Tepper links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201932
2
The Myth of Capitalism: Monopolies and the Death of Competition
201832
3 200621
4 201017
5 200214
6 202014
7 197813
8 200412
9 201610
10
Endgame: The End of the Debt SuperCycle and How It Changes Everything
20119
11 20027
12 20057
13 20224
14 20103
15 20022
16 20242
17 20232
18
FAST LEARNING NEURAL NETS WITH ADAPTIVE LEARNING STYLES
20032
19 20222
20
Characterizing the Magnetospheric State for Sawtooth Events
20151

About Jonathan Tepper

Jonathan Tepper is a scholar working on Artificial Intelligence, Management Science and Operations Research, Economics and Econometrics, Molecular Biology and General Economics, Econometrics and Finance, having authored 25 papers that have together received 207 indexed citations. Recurring topics across this work include Stock Market Forecasting Methods (8 papers), Neural Networks and Applications (4 papers), Natural Language Processing Techniques (3 papers), Neural Networks and Reservoir Computing (3 papers), Complex Systems and Time Series Analysis (3 papers), Monetary Policy and Economic Impact (3 papers), Market Dynamics and Volatility (3 papers) and Gene expression and cancer classification (3 papers). The work is most often cited by research in General Economics, Econometrics and Finance (31 citations), Management Science and Operations Research (42 citations), Artificial Intelligence (70 citations), Economics and Econometrics (52 citations) and Signal Processing (20 citations). Jonathan Tepper has collaborated with scholars based in United Kingdom, United States and Sweden. Frequent co-authors include Dominic Palmer-Brown, Jane M. Binner, Heather M. Powell, T.M. McGinnity, Mufti Mahmud, Ahmad Lotfi, Leo E. Hollister, Chris Roadknight, Kenneth L. Davis and Graham Kendall. Their work appears in journals such as Knowledge-Based Systems, Cancer, Artificial Intelligence in Medicine, Trends in Cognitive Sciences and Physica A Statistical Mechanics and its Applications.

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.

Explore authors with similar magnitude of impact