Browse by UCL people
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Number of items: 23.
Article
Goel, Akshat;
Gorse, Denise;
(2023)
A comparison of deep and shallow models for the detection of induced seismicity.
Geophysical Prospecting
10.1111/1365-2478.13386.
(In press).
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Phillips, RC;
Gorse, D;
(2018)
Cryptocurrency price drivers: Wavelet coherence analysis revisited.
PLoS One
, 13
(4)
, Article e0195200. 10.1371/journal.pone.0195200.
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Zhao, Yang;
Gorse, Denise;
(2024)
Earthquake prediction from seismic indicators using tree-based ensemble learning.
Natural Hazards
, 120
pp. 2283-2309.
10.1007/s11069-023-06221-5.
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Proceedings paper
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Gorse, Denise;
Goel, Akshat;
(2022)
Deep vs. Shallow Learning: A Benchmark Study in Low Magnitude Earthquake Detection.
In:
83rd EAGE Conference and Exhibition 2022.
(pp. pp. 1-5).
European Association of Geoscientists & Engineers: Houten, Netherlands.
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Gorse, D;
(2011)
Application of stochastic recurrent reinforcement learning to index trading.
In:
ESANN 2011 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning.
ESANN
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Kisiel, Damian;
Gorse, Denise;
(2023)
Portfolio Transformer for Attention-Based Asset Allocation.
In: Rutkowski, Leszek and Scherer, Rafał and Korytkowski, Marcin and Pedrycz, Witold and Tadeusiewicz, Ryszard and Zurada, Jacek M, (eds.)
ICAISC 2022: Artificial Intelligence and Soft Computing, PT I.
(pp. pp. 61-71).
Springer Nature Switzerland: Cham, Switzerland.
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Kisiel, Damian;
Gorse, Denise;
(2022)
A Meta-Method for Portfolio Management Using Machine Learning for Adaptive Strategy Selection.
In:
CIIS '21: Proceedings of the 2021 4th International Conference on Computational Intelligence and Intelligent Systems.
(pp. pp. 67-71).
Association for Computing Machinery (ACM): New York, NY, US.
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Kisiel, Damian;
Gorse, Denise;
(2022)
A Meta-Method for Portfolio Management Using Machine Learning for Adaptive Strategy Selection.
In:
Proceedings of the 4th International Conference on Computational Intelligence and Intelligent Systems.
Association for Computing Machinery (ACM)
(In press).
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Kisiel, Damian;
Gorse, Denise;
(2022)
Axial-LOB: High-Frequency Trading with Axial Attention.
In: Ishibuchi, H and Kwoh, CK and Tan, AH and Srinivasan, D and Miao, C and Trivedi, A and Crockett, K, (eds.)
2022 IEEE Symposium Series on Computational Intelligence (SSCI).
(pp. pp. 1327-1333).
IEEE
(In press).
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Lim, Ye-Sheen;
Gorse, Denise;
(2022)
Intra-Day Price Simulation with Generative Adversarial Modelling of the Order Flow.
In:
2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA).
IEEE: Pasadena, CA, USA.
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Lim, YS;
Gorse, D;
(2020)
Deep Recurrent Modelling of Stationary Bitcoin Price Formation Using the Order Flow.
In: Rutkowski, L and Scherer, R and Korytkowski, M and Pedrycz, W and Tadeusiewicz, R and Zurada, JM, (eds.)
ICAISC: International Conference on Artificial Intelligence and Soft Computing.
(pp. pp. 170-179).
Springer: Zakopane, Poland.
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Lim, YS;
Gorse, D;
(2020)
Deep Probabilistic Modelling of Price Movements for High-Frequency Trading.
In:
Proceedings of 2020 International Joint Conference on Neural Networks (IJCNN).
(In press).
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Lim, YS;
Gorse, D;
(2018)
Reinforcement learning for high-frequency market making.
In:
ESANN 2018 - Proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning.
(pp. pp. 521-526).
ESANN: Bruges, Belgium.
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Mann, AD;
Gorse, D;
(2017)
A New Methodology to Exploit Predictive Power in (Open, High, Low, Close) Data.
In: Lintas, A and Rovetta, S and Verschure, PFMJ and Villa, AEP, (eds.)
Artificial Neural Networks and Machine Learning – ICANN 2017: 26th International Conference on Artificial Neural Networks, Alghero, Italy, September 11-14, 2017, Proceedings, Part II.
(pp. pp. 495-502).
Springer: Cham, Switzerland.
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Mann, AD;
Gorse, D;
(2017)
Deep Candlestick Mining.
In: Liu, D and Xie, S and Li, Y and Zhao, D and El-Alfy, EM, (eds.)
Neural Information Processing: 24th International Conference, ICONIP 2017, Guangzhou, China, November 14-18, 2017, Proceedings, Part II.
(pp. pp. 913-921).
Springer: Cham, Switzerland.
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Palmer, S;
Gorse, D;
(2017)
Pseudo-analytical solutions for stochastic options pricing using monte carlo simulation and breeding PSO-trained neural networks.
In:
ESANN 2017 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning.
(pp. pp. 365-370).
i6doc.com: Bruges, Belgium.
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Palmer, S;
Gorse, D;
Muk-Pavic, E;
(2015)
Neural Networks and Particle Swarm Optimization for Function Approximation in Tri-SWACH Hull Design.
In:
Proceedings of the 16th International Conference on Engineering Applications of Neural Networks (INNS).
ACM: New York.
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Phillips, RC;
Gorse, D;
(2018)
Mutual-excitation of cryptocurrency market returns and social media topics.
In:
ICFET '18 Proceedings of the 4th International Conference on Frontiers of Educational Technologies.
(pp. pp. 80-86).
ACM: Moscow, Russian Federation.
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Phillips, RC;
Gorse, D;
(2018)
Predicting cryptocurrency price bubbles using social media data and epidemic modelling.
In:
Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence (SSCI).
(pp. pp. 394-400).
IEEE: Honolulu, HI, USA.
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Pomorski, Piotr;
Gorse, Denise;
(2023)
Improving on the Markov-Switching Regression Model by the Use of an Adaptive Moving Average.
In: Gartner, William C, (ed.)
New Perspectives and Paradigms in Applied Economics and Business.
(pp. pp. 17-30).
Springer Nature Switzerland AG: Cham, Switzerland.
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Quan, Wei;
Gorse, Denise;
(2022)
A Novel Multi-Objective Velocity-Free Boolean Particle Swarm Optimization.
In:
Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics.
(pp. pp. 2154-2160).
IEEE: Prague, Czech Republic.
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Twomey, David;
Gorse, Denise;
(2022)
ASTra: A Novel Algorithm-Level Approach to Imbalanced Classification.
In: Pimenidis, Elias and Angelov, Plamen and Jayne, Chrisina and Papaleonidas, Antonios and Aydin, Mehmet, (eds.)
Artificial Neural Networks and Machine Learning – ICANN 2022, Proceedings, Part III.
(pp. pp. 569-580).
Springer Nature Switzerland AG: Cham, Switzerland.
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Twomey, D;
Gorse, D;
(2018)
A neural network cost function for highly class-imbalanced data sets.
In:
ESANN 2018 - Proceedings 26th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine LearningESANN 2017 - Proceedings 25th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning.
(pp. pp. 207-212).
i6doc.com: Bruges, Belgium.
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