Abstract: In this paper, we propose a robust end-to-end classification model, Graph-in-Graph Neural Network (GIGNet), for automatic modulation recognition (AMR). In GIGNet, multi-level graph neural ...
Learn how backpropagation works by building it from scratch in Python! This tutorial explains the math, logic, and coding behind training a neural network, helping you truly understand how deep ...
Pea-sized brains grown in a lab have for the first time revealed the unique way neurons might misfire due to schizophrenia and bipolar disorder, psychiatric ailments that affect millions of people ...
BingoCGN employs cross-partition message quantization to summarize inter-partition message flow, which eliminates the need for irregular off-chip memory access and utilizes a fine-grained structured ...
A Spatio-Temporal Tensor Graph Neural Network-Based Method for Node-Link Prediction in Port Networks
Abstract: Port network information security has received extensive attention in recent years, in which the prediction of node links in the network is significant. A Port network is a dynamic network, ...
Positive predictive value was higher with MELD Graph compared with existing baseline algorithm. HealthDay News — A graph neural network using data from the Multicenter Epilepsy Lesion Detection (MELD) ...
Positive predictive value was higher with Multicenter Epilepsy Lesion Detection Graph compared with existing baseline algorithm. HealthDay News — A graph neural network using data from the Multicenter ...
ABSTRACT: Predicting molecular properties is essential for advancing for advancing drug discovery and design. Recently, Graph Neural Networks (GNNs) have gained prominence due to their ability to ...
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