After obtaining basic node representations for each slice through a GNN backbone, HYDG models the representations ... information propagation and aggregation by the hypergraph neural network.

Predict dynamic behaviors in a physics system in a way that's computationally efficient and adaptable to a range of scenarios.

As a longtime testing provider for large network operators, Spirent’s solutions already involve finding meaningful patterns ...

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Similarly, the hyperparameters for this model were also determined through grid search, including the dimension of hidden layers in the GNN network, the number of linear layers for fingerprint feature ...

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@article{sun2021equivariant, title={Equivariant neural network for factor graphs}, author={Sun, Fan-Yun and Kuck, Jonathan and Tang, Hao and Ermon, Stefano}, journal={arXiv preprint arXiv:2109.14218}, ...

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Impact and progress Frontiers' impact Progress Report 2022 All annual reports ...