Jun 17, 2021 · On top of that, we introduce a novel, fully modular sample selection method to select the best samples to learn from for our target prediction ...
Predicting cognitive scores with graph neural networks through sample ...
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Nov 10, 2021 · We introduce a novel, learning-based sample selection method for graph neural networks that helps to increase accuracy when predicting cognitive ...
A novel regression GNN model (namely RegGNN) for predicting IQ scores from brain connectivity is designed and inspired from the emerging graph neural ...
RegGNN, a graph neural network architecture for many-to-one regression tasks with application to functional brain connectomes for IQ score prediction.
Predicting cognitive scores with graph neural networks through sample selection learning. BRAIN IMAGING AND BEHAVIOR (2022). Overview; Write a Review. Get Full ...
We propose a novel regression graph neural network through meta-learning namely Meta-RegGNN for predicting behavioral scores from brain connectomes.
We propose two graph neural network layers for graphs with ... Predicting cognitive scores with graph neural networks through sample selection learning.
MSFEF is a dual-branch network used to extract and fuse micro-scale and macro-scale features for cognitive score prediction. Compared to state-of-the-art ...
Sep 14, 2022 · We introduce a novel meta-learning regression graph neural network that shows an exclusive ability in modeling the correlation between data and.
To address this issue, we propose two major sample selection methods to quantify the influence of a training brain multigraph on the brain multigraph population ...