Grace Y. Wang

According to our database, Grace Y. Wang authored at least 10 papers between 2015 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Prediction of Tinnitus Treatment Outcomes Based on EEG Sensors and TFI Score Using Deep Learning.

Maryam Gholami Doborjeh, Xiaoxu Liu, Zohreh Gholami Doborjeh, Yuanyuan Shen, Grant Searchfield, Philip J. Sanders, Grace Y. Wang, Alexander Sumich, Wei Qi Yan

Sensors, January, 2023

2022

Ensemble plasticity and network adaptability in SNNs.

Mahima Milinda Alwis Weerasinghe, David Parry, Grace Y. Wang, Jacqueline Whalley

CoRR, 2022

2021

Deep Learning of Explainable EEG Patterns as Dynamic Spatiotemporal Clusters and Rules in a Brain-Inspired Spiking Neural Network.

Maryam Gholami Doborjeh, Zohreh Gholami Doborjeh, Nikola K. Kasabov, Molood Barati, Grace Y. Wang

Sensors, 2021

Incorporating Structural Plasticity Approaches in Spiking Neural Networks for EEG Modelling.

Mahima Milinda Alwis Weerasinghe, Josafath Israel Espinosa Ramos, Grace Y. Wang, Dave Parry

IEEE Access, 2021

2020

Interpretability of Spatiotemporal Dynamics of the Brain Processes Followed by Mindfulness Intervention in a Brain-Inspired Spiking Neural Network Architecture.

Zohreh Gholami Doborjeh, Maryam Gholami Doborjeh, Mark Crook-Rumsey, Tamasin Taylor, Grace Y. Wang, David Moreau, Christian U. Krägeloh, Wendy Wrapson, Richard J. Siegert, Nikola K. Kasabov, Grant Searchfield, Alexander Sumich

Sensors, 2020

Brain Signal Classification Based on Deep CNN.

Terry Gao, Grace Ying Wang

Int. J. Secur. Priv. Pervasive Comput., 2020

2019

Deep Learning of EEG Data in the NeuCube Brain-Inspired Spiking Neural Network Architecture for a Better Understanding of Depression.

Dhvani Shah, Grace Y. Wang, Maryam Gholami Doborjeh, Zohreh Gholami Doborjeh, Nikola K. Kasabov

Proceedings of the Neural Information Processing - 26th International Conference, 2019

2016

A Spiking Neural Network Methodology and System for Learning and Comparative Analysis of EEG Data From Healthy Versus Addiction Treated Versus Addiction Not Treated Subjects.

Maryam Gholami Doborjeh, Grace Y. Wang, Nikola K. Kasabov, Robert Kydd, Bruce Russell

IEEE Trans. Biomed. Eng., 2016

Evolving spatio-temporal data machines based on the NeuCube neuromorphic framework: Design methodology and selected applications.

Nikola K. Kasabov, Nathan Matthew Scott, Enmei Tu, Stefan Marks, Neelava Sengupta, Elisa Capecci, Muhaini Othman, Maryam Gholami Doborjeh, Norhanifah Murli, Reggio N. Hartono, Josafath Israel Espinosa Ramos, Lei Zhou, Fahad Bashir Alvi, Grace Y. Wang, Denise Taylor, Valery Feigin, Sergei Gulyaev, Mahmoud S. Mahmoud, Zeng-Guang Hou, Jie Yang

Neural Networks, 2016

2015

Analysis of connectivity in NeuCube spiking neural network models trained on EEG data for the understanding of functional changes in the brain: A case study on opiate dependence treatment.

Elisa Capecci, Nikola K. Kasabov, Grace Y. Wang

Neural Networks, 2015