Multiscale Graph Neural Network Autoencoders for Interpretable Scientific Machine Learning.
Shivam BarweyVarun ShankarVenkatasubramanian ViswanathanRomit MaulikPublished in: CoRR (2023)
Keyphrases
- multiscale
- machine learning
- neural network
- pattern recognition
- feedforward neural networks
- data mining
- graph representation
- denoising
- wavelet transform
- artificial neural networks
- random walk
- back propagation
- machine learning algorithms
- artificial intelligence
- directed graph
- weighted graph
- image processing
- neural network model
- image segmentation
- recurrent neural networks
- decision trees
- computational intelligence
- text classification
- bipartite graph
- scientific data
- scale space
- fuzzy logic
- learning algorithm
- classification rules
- graph model
- graph matching
- inductive logic programming
- neural network is trained
- machine learning methods
- computer vision
- natural language processing
- active learning
- learning tasks
- reinforcement learning
- transfer learning
- fault diagnosis
- image fusion
- neural nets
- graph structure
- feature selection
- directed acyclic graph
- image representation
- text mining
- information extraction