| Predicting cryptocurrency price bubbles using social media data and epidemic modelling RC Phillips, D Gorse 2017 IEEE symposium series on computational intelligence (SSCI), 1-7, 2017 | 178 | 2017 |
| Prediction of the location and type of β-turns in proteins using neural networks AJ Shepherd, D Gorse, JM Thornton Protein science 8 (5), 1045-1055, 1999 | 163 | 1999 |
| Cryptocurrency price drivers: Wavelet coherence analysis revisited RC Phillips, D Gorse PloS one 13 (4), e0195200, 2018 | 162 | 2018 |
| Wavelet transforms for the characterization and detection of repeating motifs KB Murray, D Gorse, JM Thornton Journal of molecular biology 316 (2), 341-363, 2002 | 140 | 2002 |
| Morphological aspects of oligomeric protein structures H Ponstingl, T Kabir, D Gorse, JM Thornton Progress in biophysics and molecular biology 89 (1), 9-35, 2005 | 105 | 2005 |
| Learning probabilistic RAM nets using VLSI structures TG Clarkson, D Gorse, JG Taylor, CK Ng IEEE Transactions on computers 41 (12), 1552-1561, 1992 | 76 | 1992 |
| Mutual-excitation of cryptocurrency market returns and social media topics RC Phillips, D Gorse Proceedings of the 4th international conference on frontiers of educational …, 2018 | 62 | 2018 |
| On the equivalence and properties of noisy neural and probabilistic RAM nets D Gorse, JG Taylor Physics Letters A 131 (6), 326-332, 1988 | 62 | 1988 |
| An analysis of noisy RAM and neural nets D Gorse, JG Taylor Physica D: Nonlinear Phenomena 34 (1-2), 90-114, 1989 | 59 | 1989 |
| The new ERA in supervised learning D Gorse, AJ Shepherd, JG Taylor Neural Networks 10 (2), 343-352, 1997 | 56 | 1997 |
| Reinforcement learning for high-frequency market making YS Lim, D Gorse ESANN 2018-Proceedings, European Symposium on Artificial Neural Networks …, 2018 | 47 | 2018 |
| Hardware realisable models of neural processing TG Clarkson, D Gorse, JG Taylor 1989 First IEE International Conference on Artificial Neural Networks,(Conf …, 1989 | 46 | 1989 |
| A continuous input RAM-based stochastic neural model D Gorse, JG Taylor Neural Networks 4 (5), 657-665, 1991 | 43 | 1991 |
| A novel approach to the recognition of protein architecture from sequence using Fourier analysis and neural networks AJ Shepherd, D Gorse, JM Thornton Proteins: Structure, Function, and Bioinformatics 50 (2), 290-302, 2003 | 39 | 2003 |
| A general model of stochastic neural processing D Gorse, JG Taylor Biological Cybernetics 63 (4), 299-306, 1990 | 36 | 1990 |
| Application of stochastic recurrent reinforcement learning to index trading D Gorse ESANN, 2011 | 31 | 2011 |
| Speaker identification for security systems using reinforcement-trained pRAM neural network architectures TG Clarkson, CC Christodoulou, Y Guan, D Gorse, DA Romano-Critchley, ... IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and …, 2001 | 30 | 2001 |
| Generalization in probabilistic RAM nets TG Clarkson, Y Guan, JG Taylor, D Gorse IEEE Transactions on Neural Networks 4 (2), 360-363, 1993 | 30 | 1993 |
| A classical algorithm for avoiding local minima D Gorse, A Shepherd, JG Taylor Proceedings of the World Congress on Neural Networks, 364-369, 1994 | 23 | 1994 |
| From wetware to hardware: reverse engineering using probabilistic RAMs TG Clarkson, D Gorse, JG Taylor Journal of intelligent systems 2 (1-4), 11-30, 1992 | 23 | 1992 |
Adrian J ShepherdEmeritus Professor of Computational Biology, Birkbeck, University of LondonEmail verificata su mail.cryst.bbk.ac.uk
