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Found 3 papers, 1 papers with code
Graph Neural Network for spatiotemporal data: methods and applications
Graph neural networks (GNNs) have emerged as a powerful tool for modeling and understanding data with dependencies to each other such as spatial and temporal dependencies.
Going Beyond XAI: A Systematic Survey for Explanation-Guided Learning
As the societal impact of Deep Neural Networks (DNNs) grows, the goals for advancing DNNs become more complex and diverse, ranging from improving a conventional model accuracy metric to infusing advanced human virtues such as fairness, accountability, transparency (FaccT), and unbiasedness.
Explainable artificial intelligence
Explainable Artificial Intelligence (XAI)
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Deep Spatial Domain Generalization
Spatial domain generalization is a spatial extension of domain generalization, which can generalize to unseen spatial domains in continuous 2D space.
