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Found 3 papers, 1 papers with code
Spatio-Temporal Attention Graph Neural Network for Remaining Useful Life Prediction
Our model combines graph neural networks and temporal convolutional neural networks for spatial and temporal feature extraction, respectively.
Fast Bayesian Updates for Deep Learning with a Use Case in Active Learning
Retraining deep neural networks when new data arrives is typically computationally expensive.
Design of Explainability Module with Experts in the Loop for Visualization and Dynamic Adjustment of Continual Learning
With the help of this module, experts can be more confident in decision-making regarding anomaly filtering, dynamic adjustment of hyperparameters, data backup, etc.
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