A General Framework for quantifying Aleatoric and Epistemic uncertainty in Graph Neural Networks.
Sai MunikotiDeepesh AgarwalLaya DasBalasubramaniam NatarajanPublished in: CoRR (2022)
Keyphrases
- neural network
- graph representation
- artificial neural networks
- pattern recognition
- directed graph
- fuzzy systems
- recurrent neural networks
- graph model
- graph theoretic
- fuzzy logic
- random walk
- connected components
- weighted graph
- graph structure
- graph theory
- genetic algorithm
- associative memory
- multi layer
- graph matching
- directed acyclic graph
- neural nets
- back propagation
- decision theory
- belief change
- graph construction
- robust optimization
- possibility theory
- probability theory
- decision making
- pairwise
- spanning tree
- belief functions
- graph mining