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Fairbank, Michael and Prokhorov, Danil and Barragan-Alcantar, David and Samothrakis, Spyridon and Li, Shuhui (2025) Neurocontrol for Fixed-Length Trajectories in Environments with Soft Barriers. Neural Networks, 184. p. 107034. DOI https://doi.org/10.1016/j.neunet.2024.107034

Farhatullah and Chen, Xin and Zeng, Deze and Ullah, Rahmat and Nawaz, Rab and Xu, Jiafeng and Arslan, Tughrul (2025) A deep learning approach for non-invasive Alzheimer's monitoring using microwave radar data. Neural Networks, 181. p. 106778. DOI https://doi.org/10.1016/j.neunet.2024.106778

Li, Shurui and Daly, Ian and Guan, Cuntai and Cichocki, Andrzej and Jin, Jing (2024) Inter-participant transfer learning with attention based domain adversarial training for P300 detection. Neural Networks, 180. p. 106655. DOI https://doi.org/10.1016/j.neunet.2024.106655

Yilmaz, Ahmet and Poli, Riccardo (2022) Successfully and Efficiently Training Deep Multi-layer Perceptrons with Logistic Activation Function Simply Requires Initializing the Weights with an Appropriate Negative Mean. Neural Networks, 153. pp. 87-103. DOI https://doi.org/10.1016/j.neunet.2022.05.030

Venugopal, Rohit and Shafqat, Noman and Venugopal, Ishwar and Tillbury, Benjamin Mark John and Stafford, Harry Demetrios and Bourazeri, Aikaterini (2022) Privacy preserving Generative Adversarial Networks to model Electronic Health Records. Neural Networks, 153. pp. 339-348. DOI https://doi.org/10.1016/j.neunet.2022.06.022

Lonnqvist, Ben and Clarke, Alasdair DF and Chakravarthi, Ramakrishna (2020) Crowding in humans is unlike that in convolutional neural networks. Neural Networks, 126. pp. 262-274. DOI https://doi.org/10.1016/j.neunet.2020.03.021

Jin, Jing and Miao, Yangyang and Daly, Ian and Zuo, Cili and Hu, Dewen and Cichocki, Andrzej (2019) Correlation-based channel selection and regularized feature optimization for MI-based BCI. Neural Networks, 118. pp. 262-270. DOI https://doi.org/10.1016/j.neunet.2019.07.008

Ognibene, Dimitri and Fiore, Vincenzo G and Gu, Xiaosi (2019) Addiction beyond pharmacological effects: The role of environment complexity and bounded rationality. Neural Networks, 116. pp. 269-278. DOI https://doi.org/10.1016/j.neunet.2019.04.022

Antonopoulos, Chris G and Martinez-Bianco, Ezequiel and Baptista, Murilo (2019) Evaluating performance of neural codes in model neural communication networks. Neural Networks, 109. pp. 90-102. DOI https://doi.org/10.1016/j.neunet.2018.10.008

Feng, J and Yin, E and Jin, J and Saab, R and Daly, Ian and Wang, X and Hu, D and Cichocki, A (2018) Towards correlation-based time window selection method for motor imagery BCIs. Neural Networks, 102. pp. 87-95. DOI https://doi.org/10.1016/j.neunet.2018.02.011

Borges, RR and Borges, FS and Lameu, EL and Batista, AM and Iarosz, KC and Caldas, IL and Antonopoulos, Chris G and Baptista, MS (2017) Spike timing-dependent plasticity induces non-trivial topology in the brain. Neural Networks, 88. pp. 58-64. DOI https://doi.org/10.1016/j.neunet.2017.01.010

Fairbank, Michael and Li, Shuhui and Fu, Xingang and Alonso, Eduardo and Wunsch, Donald (2014) An adaptive recurrent neural-network controller using a stabilization matrix and predictive inputs to solve a tracking problem under disturbances. Neural Networks, 49. pp. 74-86. DOI https://doi.org/10.1016/j.neunet.2013.09.010

Yoon, Ji Won and Roberts, Stephen J and Dyson, Mathew and Gan, John Q (2011) Bayesian inference for an adaptive Ordered Probit model: An application to Brain Computer Interfacing. Neural Networks, 24 (7). pp. 726-734. DOI https://doi.org/10.1016/j.neunet.2011.03.019

Foulsham, Tom and Barton, Jason JS and Kingstone, Alan and Dewhurst, Richard and Underwood, Geoffrey (2011) Modeling eye movements in visual agnosia with a saliency map approach: Bottom?up guidance or top?down strategy? Neural Networks, 24 (6). pp. 665-677. DOI https://doi.org/10.1016/j.neunet.2011.01.004

Yoon, Ji Won and Roberts, Stephen J and Dyson, Matt and Gan, John Q (2009) Adaptive classification for Brain Computer Interface systems using Sequential Monte Carlo sampling. Neural Networks, 22 (9). pp. 1286-1294. DOI https://doi.org/10.1016/j.neunet.2009.06.005