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Found 2 papers, 2 papers with code
Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks
We explore a new direction in that we can capture the evolving dynamics of temporal graphs with spiking neural networks (SNNs) instead of RNNs.
Tensor Decomposition with Relational Constraints for Predicting Multiple Types of MicroRNA-disease Associations
To this end, we innovatively represent miRNA-disease-type triplets as a tensor and introduce Tensor Decomposition methods to solve the prediction task.
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