Systematic review of teleoperated endovascular robots finds navigation feasible over 7000 km with 30-163 ms latency and 100% success in small human trials, mostly from animal and phantom models.
Park, K Yoon, Degree Matters: Assessing the Generalization of Graph Neural Network, 7th 34 IEEE Int
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A probabilistic graphical model framework with graph neural network inference computes Bayesian posteriors for discrete structural states, claimed to match traditional Bayesian results while scaling to high-dimensional problems via topology-informed learning and scale-adaptive training.
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Probabilistic Graphical Model using Graph Neural Networks for Bayesian Inversion of Discrete Structural Component States
A probabilistic graphical model framework with graph neural network inference computes Bayesian posteriors for discrete structural states, claimed to match traditional Bayesian results while scaling to high-dimensional problems via topology-informed learning and scale-adaptive training.