Denise Gorse
Impact in
- Artificial Intelligence top 5%
- Neural Networks and Applications
Papers in
-
- Neural Networks and Applications 25
- Evolutionary Algorithms and Applications 7
-
- Stock Market Forecasting Methods 13
- Co-authors
- John G. Taylor (20 shared papers)Janet M. Thornton (5 shared papers)Adrian J. Shepherd (5 shared papers)T.G. Clarkson (14 shared papers)J.G. Taylor (4 shared papers)Hannes Ponstingl (1 shared paper)Jonathon Taylor (1 shared paper)Chris C. Christodoulou (2 shared papers)
- Journals
- Neural Networks (3 papers)Biopolymers (2 papers)Progress in Biophysics and Molecular Biology (2 papers)Physica D Nonlinear Phenomena (1 paper)Protein Science (1 paper)
- Partner nations
- United KingdomUnited States
In The Last Decade
Denise Gorse
55 papers receiving 888 citations
Peers
Comparison fields: 5 of 102
- Artificial Intelligence 336
- Management Science and Operations Research 98
- Finance 70
- Information Systems 151
- Economics and Econometrics 147
Countries citing papers authored by Denise Gorse
This map shows the geographic impact of Denise Gorse'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 Denise Gorse with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Denise Gorse more than expected).
Fields of papers citing papers by Denise Gorse
This network shows the impact of papers produced by Denise Gorse. 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 Denise Gorse. The network helps show where Denise Gorse may publish in the future.
Co-authors
The 12 scholars most cited alongside Denise Gorse, 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 61 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 105 | |
| 2 | 1999 | 98 | |
| 3 | 2017 | 92 | |
| 4 | 2002 | 78 | |
| 5 | 2004 | 66 | |
| 6 | 1992 | 42 | |
| 7 | 1989 | 33 | |
| 8 | 1991 | 32 | |
| 9 | 1997 | 32 | |
| 10 | 1988 | 30 | |
| 11 | 2002 | 26 | |
| 12 | Hardware realisable models of neural processing | 1989 | 25 |
| 13 | 2001 | 22 | |
| 14 | 1990 | 21 | |
| 15 | Application of stochastic recurrent reinforcement learning to index trading | 2011 | 18 |
| 16 | 1992 | 15 | |
| 17 | 1992 | 15 | |
| 18 | 1993 | 14 | |
| 19 | 2001 | 14 | |
| 20 | 2002 | 14 |
About Denise Gorse
Denise Gorse is a scholar working on Artificial Intelligence, Management Science and Operations Research, Cognitive Neuroscience, Finance and Economics and Econometrics, having authored 61 papers that have together received 932 indexed citations. Recurring topics across this work include Neural Networks and Applications (25 papers), Neural dynamics and brain function (14 papers), Stock Market Forecasting Methods (13 papers), Advanced Memory and Neural Computing (8 papers), Financial Markets and Investment Strategies (8 papers), Evolutionary Algorithms and Applications (7 papers), Market Dynamics and Volatility (7 papers) and Protein Structure and Dynamics (7 papers). The work is most often cited by research in Artificial Intelligence (336 citations), Management Science and Operations Research (98 citations), Finance (70 citations), Information Systems (151 citations) and Economics and Econometrics (147 citations). Denise Gorse has collaborated with scholars based in United Kingdom and United States. Frequent co-authors include John G. Taylor, Janet M. Thornton, Adrian J. Shepherd, T.G. Clarkson, J.G. Taylor, Hannes Ponstingl, Jonathon Taylor, Chris C. Christodoulou, Yang Zhao and Herwig Ponstingl. Their work appears in journals such as Neural Networks, Biopolymers, Progress in Biophysics and Molecular Biology, Physica D Nonlinear Phenomena and Protein Science.
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.