John Moody

10.2k citations
50 papers · 6.8k indexed · 3 hit papers · h-index 27

John Moody

49 papers receiving 6.3k citations

Hit Papers

Proceedings of the 3rd International Conference on Neural...928198420261998201250010001.5k2.0k2.5k

Peers

John Moody
Comparison fields: 5 of 188
  • Artificial Intelligence 3.4k
  • Computer Vision and Pattern Recognition 1.2k
  • Management Science and Operations Research 712
  • Signal Processing 602
  • Control and Systems Engineering 1.1k
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Citations per field
00.5×1.5×
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Citations per year

Countries citing papers authored by John Moody

Since Specialization
Citations

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

Fields of papers citing papers by John Moody

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20225
2 20182
3
Stochastic Direct Reinforcement: Application to Simple Games with Recurrence.
20047
4 2003116
5 200238
6 200211
7 200264
8
Developments in forecast combination and portfolio choice
200135
9 2001272
10
Decision technologies for computational finance : proceedings of the Fifth International Conference Computational Finance
19982
11
The Effective Number of Parameters: An Analysis of Generalization and Regularization in Nonlinear Learning Systems
1991318
12
Principled Architecture Selection for Neural Networks: Application to Corporate Bond Rating Prediction
199166
13
Networks with Learned Unit Response Functions
199121
14
Towards Faster Stochastic Gradient Search
199164
15
Note on Learning Rate Schedules for Stochastic Optimization
199093
16 1990118
17
Note on Development of Modularity in Simple Cortical Models
19893
18
Fast Learning in Multi-Resolution Hierarchies
1988103
19 198891
20
Computable functions and complexity in neural networks
19872

About John Moody

John Moody is a scholar working on Management Science and Operations Research, Artificial Intelligence, Signal Processing, Finance and Sensory Systems, having authored 50 papers that have together received 6.8k indexed citations. Recurring topics across this work include Neural Networks and Applications (18 papers), Stock Market Forecasting Methods (11 papers), Complex Systems and Time Series Analysis (8 papers), Blind Source Separation Techniques (6 papers), Financial Markets and Investment Strategies (5 papers), Neural dynamics and brain function (4 papers), Model Reduction and Neural Networks (4 papers) and Stochastic Gradient Optimization Techniques (4 papers). The work is most often cited by research in Artificial Intelligence (3.4k citations), Computer Vision and Pattern Recognition (1.2k citations), Management Science and Operations Research (712 citations), Signal Processing (602 citations) and Control and Systems Engineering (1.1k citations). John Moody has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Christian J. Darken, Richard P. Lippmann, David S. Touretzky, Frank Wilczek, Matthew Saffell, Howard H. Yang, Chris Darken, Lizhong Wu, Alfred D. Shapere and Lawrence M. Krauss. Their work appears in journals such as Neural Computation, Journal of Forecasting, Physical Review Letters, The Astrophysical Journal and Neural Networks.

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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