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ORCIDDenise Gorse
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2020 – today
- 2020
[c20]Ye-Sheen Lim, Denise Gorse:
Deep Recurrent Modelling of Stationary Bitcoin Price Formation Using the Order Flow. ICAISC (1) 2020: 170-179- [c19]Ye-Sheen Lim, Denise Gorse:
Deep Probabilistic Modelling of Price Movements for High-Frequency Trading. IJCNN 2020: 1-8 - [i3]Ye-Sheen Lim, Denise Gorse:
Deep Probabilistic Modelling of Price Movements for High-Frequency Trading. CoRR abs/2004.01498 (2020) - [i2]Ye-Sheen Lim, Denise Gorse:
Deep Recurrent Modelling of Stationary Bitcoin Price Formation Using the Order Flow. CoRR abs/2004.01499 (2020)
2010 – 2019
- 2018
- [c18]Ye-Sheen Lim, Denise Gorse:
Reinforcement Learning for High-Frequency Market Making. ESANN 2018 - [c17]David Twomey, Denise Gorse:
A neural network cost function for highly class-imbalanced data sets. ESANN 2018 - [i1]Ross C. Phillips, Denise Gorse:
Mutual-Excitation of Cryptocurrency Market Returns and Social Media Topics. CoRR abs/1806.11093 (2018) - 2017
- [c16]Sam Palmer, Denise Gorse:
Pseudo-analytical solutions for stochastic options pricing using Monte Carlo simulation and Breeding PSO-trained neural networks. ESANN 2017 - [c15]Andrew D. Mann, Denise Gorse:
A New Methodology to Exploit Predictive Power in (Open, High, Low, Close) Data. ICANN (2) 2017: 495-502 - [c14]Andrew D. Mann, Denise Gorse:
Deep Candlestick Mining. ICONIP (2) 2017: 913-921 - [c13]Ross C. Phillips, Denise Gorse:
Predicting cryptocurrency price bubbles using social media data and epidemic modelling. SSCI 2017: 1-7 - 2015
- [c12]Sam Palmer, Denise Gorse, Ema Muk-Pavic:
Neural Networks and Particle Swarm Optimization for Function Approximation in Tri-SWACH Hull Design. EANN Workshops 2015: 8:1-8:6 - [c11]Pascal Khoury, Denise Gorse:
Trading Optimally Diversified Portfolios in Emerging Markets with Neuro-Particle Swarm Optimisation. ICONIP (2) 2015: 52-60 - [c10]Pascal Khoury, Denise Gorse:
Investing in emerging markets using neural networks and particle swarm optimisation. IJCNN 2015: 1-7 - 2013
- [c9]Denise Gorse:
Binary particle swarm optimisation with improved scaling behaviour. ESANN 2013 - [c8]Marzieh Saeidi, Denise Gorse:
A Novel Application of Particle Swarm Optimisation to Optimal Trade Execution. ICONIP (2) 2013: 448-455 - [c7]Pascal Khoury, Denise Gorse:
Investigation of the Predictability of Steel Manufacturer Stock Price Movements Using Particle Swarm Optimisation. ICONIP (2) 2013: 673-680 - 2012
- [c6]Marta Díez-Fernández, Sergio Alvarez Teleña, Denise Gorse:
Construction of Emerging Markets Exchange Traded Funds Using Multiobjective Particle Swarm Optimisation. ICANN (2) 2012: 140-147 - [c5]Pascal Khoury, Denise Gorse:
Identification of Factors Characterising Volatility and Firm-Specific Risk Using Ensemble Classifiers. ICONIP (4) 2012: 450-457 - [c4]Jean Krohn, Denise Gorse:
Extracting Key Gene Regulatory Dynamics for the Direct Control of Mechanical Systems. PPSN (1) 2012: 468-477 - 2011
- [c3]Denise Gorse:
Application of stochastic recurrent reinforcement learning to index trading. ESANN 2011 - 2010
- [c2]Jean Krohn, Denise Gorse:
Fractal Gene Regulatory Networks for Control of Nonlinear Systems. PPSN (2) 2010: 209-218
1990 – 1999
- 1997
- [j7]Denise Gorse, David A. Romano-Critchley, John G. Taylor:
A pulse-based reinforcement algorithm for learning continuous functions. Neurocomputing 14(4): 319-344 (1997) - [j6]Denise Gorse, Adrian J. Shepherd
, John G. Taylor:
The New ERA in Supervised Learning. Neural Networks 10(2): 343-352 (1997) - 1995
- [j5]Trevor G. Clarkson, John G. Taylor, Denise Gorse:
Response to letter by K. Gurney. Neural Networks 8(3): 491- (1995) - 1994
- [j4]Yelin Guan, Trevor G. Clarkson, John G. Taylor, Denise Gorse:
Noisy reinforcement training for pRAM nets. Neural Networks 7(3): 523-528 (1994) - 1993
- [j3]Trevor G. Clarkson, Yelin Guan, John G. Taylor, Denise Gorse:
Generalization in probabilistic RAM nets. IEEE Trans. Neural Networks 4(2): 360-363 (1993) - [c1]Denise Gorse, Adrian J. Shepherd, John G. Taylor:
Traking global minima using a range expansion algorithm. ESANN 1993 - 1992
- [j2]Trevor G. Clarkson, Denise Gorse, John G. Taylor, C. K. Ng:
Learning Probabilistic RAM Nets Using VLSI Structures. IEEE Trans. Computers 41(12): 1552-1561 (1992) - 1991
- [j1]Denise Gorse, John G. Taylor:
A continuous input RAM-based stochastic neural model. Neural Networks 4(5): 657-665 (1991)
Coauthor Index
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