Eric B. Baum
Impact in
- Artificial Intelligence top 0.5%
- Neural Networks and Applications
- Machine Learning and Algorithms
- Evolutionary Algorithms and Applications
- Metaheuristic Optimization Algorithms Research
- Machine Learning and Data Classification
Papers in
-
- Machine Learning and Algorithms 12
- Neural Networks and Applications 9
- Evolutionary Algorithms and Applications 7
- Artificial Intelligence in Games 6
- Metaheuristic Optimization Algorithms Research 5
- Machine Learning and Data Classification 5
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- Computability, Logic, AI Algorithms 9
- Co-authors
- David H. Haussler (1 shared paper)Dan Boneh (3 shared papers)Charles Garrett (2 shared papers)Frank Wilczek (2 shared papers)Richard B. Lipton (1 shared paper)John E. Moody (1 shared paper)Kevin Lang (1 shared paper)Gary William Flake (1 shared paper)
- Journals
- Neural Computation (7 papers)Physical Review Letters (3 papers)Journal of Complexity (2 papers)Machine Learning (1 paper)Artificial Intelligence (1 paper)
- Partner nations
- United StatesHong Kong
In The Last Decade
Eric B. Baum
49 papers receiving 3.0k citations
Eric B. Baum's Hit Papers
Peers
Comparison fields: 5 of 170
- Artificial Intelligence 2.0k
- Computational Theory and Mathematics 420
- Computer Vision and Pattern Recognition 491
- Signal Processing 223
- Control and Systems Engineering 310
Countries citing papers authored by Eric B. Baum
This map shows the geographic impact of Eric B. Baum'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 Eric B. Baum with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric B. Baum more than expected).
Fields of papers citing papers by Eric B. Baum
This network shows the impact of papers produced by Eric B. Baum. 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 Eric B. Baum. The network helps show where Eric B. Baum may publish in the future.
Co-authors
The 22 scholars most cited alongside Eric B. Baum, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 53 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | What Size Net Gives Valid Generalization? Hit paper breakdown → | 1989 | 1267 |
| 2 | 1988 | 286 | |
| 3 | 1995 | 262 | |
| 4 | 1991 | 131 | |
| 5 | Supervised Learning of Probability Distributions by Neural Networks | 1987 | 121 |
| 6 | 1995 | 120 | |
| 7 | 1983 | 119 | |
| 8 | 1988 | 102 | |
| 9 | 1996 | 92 | |
| 10 | 2003 | 78 | |
| 11 | 1989 | 66 | |
| 12 | 1990 | 63 | |
| 13 | Constructing Hidden Units using Examples and Queries | 1990 | 62 |
| 14 | 1990 | 57 | |
| 15 | 2002 | 51 | |
| 16 | 1997 | 38 | |
| 17 | 1999 | 34 | |
| 18 | 1998 | 32 | |
| 19 | 1986 | 28 | |
| 20 | 1990 | 25 |
About Eric B. Baum
Eric B. Baum is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Signal Processing, Mathematical Physics and Economics and Econometrics, having authored 53 papers that have together received 3.3k indexed citations. Recurring topics across this work include Machine Learning and Algorithms (12 papers), Computability, Logic, AI Algorithms (9 papers), Neural Networks and Applications (9 papers), Evolutionary Algorithms and Applications (7 papers), Artificial Intelligence in Games (6 papers), DNA and Biological Computing (6 papers), Metaheuristic Optimization Algorithms Research (5 papers) and Machine Learning and Data Classification (5 papers). The work is most often cited by research in Artificial Intelligence (2.0k citations), Computational Theory and Mathematics (420 citations), Computer Vision and Pattern Recognition (491 citations), Signal Processing (223 citations) and Control and Systems Engineering (310 citations). Eric B. Baum has collaborated with scholars based in United States and Hong Kong. Frequent co-authors include David H. Haussler, Dan Boneh, Charles Garrett, Frank Wilczek, Richard B. Lipton, John E. Moody, Kevin Lang, Gary William Flake, Warren D. Smith and Igor Đurđanović. Their work appears in journals such as Neural Computation, Physical Review Letters, Journal of Complexity, Machine Learning and Artificial Intelligence.
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.