Grace Y. Wang
lecturer in psychology at University of Southern Queensland
Facts
8 properties- Instance of
- human
- Occupation
- researcher, psychologist
- Doctoral student
- Zohreh Doborjeh[6]
- On focus list of Wikimedia project
- NZThesisProject[9]
🏷️ Also known as
en Grace Wang
en Grace Y. Wang
en G. Wang
en Ying Wang
🔖 Identifiers · 9
- ORCID iD
- 0000-0003-2063-031X
- OpenAlex ID
- A5100774729
- DBLP author ID
- 163/6556
- Google Knowledge Graph ID
- /g/11f65d6n7x
- Google Scholar author ID
- ITPGXvIAAAAJ
- Loop ID
- 324435
- Mendeley person ID
- grace-wang31
- ResearchGate profile ID
- Grace-Wang-29
- Scopus author ID
- 55635271000
🔗 Connections
Author of 11
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,
An implementation model for managing cloud-based longitudinal care plans for children with medical complexity,
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,
Deep Learning of Explainable EEG Patterns as Dynamic Spatiotemporal Clusters and Rules in a Brain-Inspired Spiking Neural Network,
Evolving spatio-temporal data machines based on the NeuCube neuromorphic framework: Design methodology and selected applications,
Incorporating Structural Plasticity Approaches in Spiking Neural Networks for EEG Modelling,
Interpretability of Spatiotemporal Dynamics of the Brain Processes Followed by Mindfulness Intervention in a Brain-Inspired Spiking Neural Network Architecture,
Prediction of Tinnitus Treatment Outcomes Based on EEG Sensors and TFI Score Using Deep Learning
+3 more
← Authored by 11
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,
An implementation model for managing cloud-based longitudinal care plans for children with medical complexity,
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,
Deep Learning of Explainable EEG Patterns as Dynamic Spatiotemporal Clusters and Rules in a Brain-Inspired Spiking Neural Network,
Evolving spatio-temporal data machines based on the NeuCube neuromorphic framework: Design methodology and selected applications,
Incorporating Structural Plasticity Approaches in Spiking Neural Networks for EEG Modelling,
Interpretability of Spatiotemporal Dynamics of the Brain Processes Followed by Mindfulness Intervention in a Brain-Inspired Spiking Neural Network Architecture,
Prediction of Tinnitus Treatment Outcomes Based on EEG Sensors and TFI Score Using Deep Learning
+3 more
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