Search Results for author:
Found 4 papers, 2 papers with code
Hypergraph Transformer for Semi-Supervised Classification
Hypergraphs play a pivotal role in the modelling of data featuring higher-order relations involving more than two entities.
Explainable fMRI-based Brain Decoding via Spatial Temporal-pyramid Graph Convolutional Network
The results show that STpGCN significantly improves brain decoding performance compared to competing baseline models; BrainNetX successfully annotates task-relevant brain regions.
Immunofluorescence Capillary Imaging Segmentation: Cases Study
Our work offers a benchmark dataset for training deep learning models for capillary image segmentation and provides a potential tool for future capillary research.
Deep Auto-encoder with Neural Response
In this study, we propose an integrated framework called Deep Autoencoder with Neural Response (DAE-NR), which incorporates information from ANN and the visual cortex to achieve better image reconstruction performance and higher neural representation similarity between biological and artificial neurons.
