PGM-Explainer: Probabilistic Graphical Model Explanations for Graph Neural Networks.
Minh N. VuMy T. ThaiPublished in: NeurIPS (2020)
Keyphrases
- probabilistic graphical models
- neural network
- graphical models
- application to image segmentation
- markov networks
- soft computing
- first order logic
- latent variables
- conditional random fields
- approximate inference
- belief propagation
- probabilistic inference
- random variables
- pattern recognition
- parameter learning
- artificial neural networks
- exact inference
- belief functions
- hidden variables
- back propagation
- directed acyclic graph
- fuzzy logic
- maximum likelihood
- causal models
- least squares
- machine learning