A large-scale standardized benchmark of GNN attacks and defenses reveals that target node selection and attacked-model training process can completely distort measured attack effectiveness.
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An analytical channel impulse response for dispersive closed-loop molecular communication with pulsatile flow is derived as a wrapped normal distribution with time-variant mean and variance.
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Adversarial Graph Neural Network Benchmarks: Towards Practical and Fair Evaluation
A large-scale standardized benchmark of GNN attacks and defenses reveals that target node selection and attacked-model training process can completely distort measured attack effectiveness.
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Analytical Modeling of Dispersive Closed-loop MC Channels with Pulsatile Flow
An analytical channel impulse response for dispersive closed-loop molecular communication with pulsatile flow is derived as a wrapped normal distribution with time-variant mean and variance.