Learn how to find datasets, notebooks, competitions, and courses on Kaggle that can help you with neural network techniques for machine learning.

Heterogeneous graph neural network learning hopes to express meaningful graph information through the neural network. Based on the obtained graph information to be applied to connection prediction, ...

How to train a neural network model that can perform graph-level predictions when the memory required to train the model on a single graph may not fit on a single device? How to make a model ...

Power flow analysis plays a crucial role in examining the electricity flow within a power system network. By performing power flow calculations, the system's steady-state variables, including voltage ...

NN4G is a constructive neural network for graphs defined in Micheli, Alessio. "Neural network for graphs: A contextual constructive approach." IEEE Transactions on Neural Networks 20.3 (2009): 498-511 ...

The Mithra system uses an internal neural network graph model with 3.5 billion nodes and 48 billion edges to spot and rank the trustworthiness of domains and identify potential threats.