Controllable data generation by deep learning: A review

S Wang, Y Du, X Guo, B Pan, Z Qin, L Zhao - ACM Computing Surveys, 2024‏ - dl.acm.org
Designing and generating new data under targeted properties has been attracting various
critical applications such as molecule design, image editing and speech synthesis …

Braingb: a benchmark for brain network analysis with graph neural networks

H Cui, W Dai, Y Zhu, X Kan, AAC Gu… - IEEE transactions on …, 2022‏ - ieeexplore.ieee.org
Map** the connectome of the human brain using structural or functional connectivity has
become one of the most pervasive paradigms for neuroimaging analysis. Recently, Graph …

Brain network transformer

X Kan, W Dai, H Cui, Z Zhang… - Advances in Neural …, 2022‏ - proceedings.neurips.cc
Human brains are commonly modeled as networks of Regions of Interest (ROIs) and their
connections for the understanding of brain functions and mental disorders. Recently …

Interpretable graph neural networks for connectome-based brain disorder analysis

H Cui, W Dai, Y Zhu, X Li, L He, C Yang - International Conference on …, 2022‏ - Springer
Human brains lie at the core of complex neurobiological systems, where the neurons,
circuits, and subsystems interact in enigmatic ways. Understanding the structural and …

Lingcn: Structural linearized graph convolutional network for homomorphically encrypted inference

H Peng, R Ran, Y Luo, J Zhao… - Advances in …, 2023‏ - proceedings.neurips.cc
Abstract The growth of Graph Convolution Network (GCN) model sizes has revolutionized
numerous applications, surpassing human performance in areas such as personal …

Autorep: Automatic relu replacement for fast private network inference

H Peng, S Huang, T Zhou, Y Luo… - Proceedings of the …, 2023‏ - openaccess.thecvf.com
The growth of the Machine-Learning-As-A-Service (MLaaS) market has highlighted clients'
data privacy and security issues. Private inference (PI) techniques using cryptographic …

[HTML][HTML] Explainable spatio-temporal graph neural networks for multi-site photovoltaic energy production

A Verdone, S Scardapane, M Panella - Applied Energy, 2024‏ - Elsevier
In recent years, there has been a growing demand for renewable energy sources, which are
inherently associated with a decentralized distribution and dependent on weather …

Community-aware transformer for autism prediction in fmri connectome

A Bannadabhavi, S Lee, W Deng, R Ying… - … Conference on Medical …, 2023‏ - Springer
Autism spectrum disorder (ASD) is a lifelong neurodevelopmental condition that affects
social communication and behavior. Investigating functional magnetic resonance imaging …

On positional and structural node features for graph neural networks on non-attributed graphs

H Cui, Z Lu, P Li, C Yang - Proceedings of the 31st ACM International …, 2022‏ - dl.acm.org
Graph neural networks (GNNs) have been widely used in various graph-related problems
such as node classification and graph classification, where the superior performance is …

[HTML][HTML] The combination of a graph neural network technique and brain imaging to diagnose neurological disorders: a review and outlook

S Zhang, J Yang, Y Zhang, J Zhong, W Hu, C Li… - Brain Sciences, 2023‏ - mdpi.com
Neurological disorders (NDs), such as Alzheimer's disease, have been a threat to human
health all over the world. It is of great importance to diagnose ND through combining artificial …