Graph wavelet neural network

1. What is a wavelet neural network?
2. Is GNN better than CNN?
3. How GNN is different from CNN?
4. What is graph based neural network?

What is a wavelet neural network?

Wavelet networks are a new class of networks that combine the classic sigmoid neural networks (NNs) and the wavelet analysis (WA). WNs have been used with great success in a wide range of applications. However a general accepted framework for applying WNs is missing from the literature.

Is GNN better than CNN?

GNN is the solution to the limitation of Convolutional Neural Networks (CNN) as CNNs fail on graphs. CNN's are very useful in tasks like image classification, image recognition, or object detection.

How GNN is different from CNN?

The major difference between CNNs and GNNs is that CNNs are specially built to operate on regular (Euclidean) structured data, while GNNs are the generalized version of CNNs where the numbers of nodes connections vary and the nodes are unordered (irregular on non-Euclidean structured data).

What is graph based neural network?

GNNs apply the predictive power of deep learning to rich data structures that depict objects and their relationships as points connected by lines in a graph. October 24, 2022 by Rick Merritt.