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Found 3 papers, 1 papers with code
Fraud Detection with Binding Global and Local Relational Interaction
Apart from the Transformer-based network, we further introduce a Relation-Aware GNN module to learn global embeddings, which is later merged into the local embeddings by an attention fusion module and a skip connection.
GPINN: Physics-informed Neural Network with Graph Embedding
This work proposes a Physics-informed Neural Network framework with Graph Embedding (GPINN) to perform PINN in graph, i. e. topological space instead of traditional Euclidean space, for improved problem-solving efficiency.
Self-Supervised Decomposition, Disentanglement and Prediction of Video Sequences while Interpreting Dynamics: A Koopman Perspective
Human interpretation of the world encompasses the use of symbols to categorize sensory inputs and compose them in a hierarchical manner.
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