Oct 3, 2018 � This work proposes a graph generation system based on scattering and demonstrates competitive performance as well as indicates better promise of the�...
Oct 12, 2021 � We propose a representation-first approach to molecular graph generation. We guide the latent representation of an autoencoder by capturing graph structure�...
Generative networks have made it possible to generate meaningful signals such as images and texts from simple noise. Recently, generative methods based on�...
Oct 12, 2021 � We guide the latent representation of an autoencoder by capturing graph structure information with the geometric scattering transform and apply�...
• Experiment: Generate a graph by a Stochastic Block Model, randomly select two vertices and perform “graph surgery”, then record. Page 44. Robustness to�...
Oct 3, 2018 � The scattering transform can be used as an encoder for generating both the graph and the signal on it. We train two MLP's D1and D2, where both�...
We adopt a similar method, using a graph scattering transform as an encoder for graph signals, which is robust to signal and graph manipulations, and train�...
Abstract: We generalize the scattering transform to graphs and consequently construct a convolutional neural network on graphs. We further use it to form a�...
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What is the scattering number of a graph?
Sep 23, 2022 � graph are encoded using scattering transforms, and then passed as inputs into machine learning models First, we have our input graph, which�...
We generalize the scattering transform to graphs and consequently construct a convolutional neural network on graphs.
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