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A Comprehensive Survey of Dynamic Graph Neural Networks: Models, Frameworks, Benchmarks, Experiments and Challenges
From the analysis and evaluation results, we identify key challenges and offer principles for future research to enhance the design of models and frameworks in the dynamic GNNs field.
Importance-Aware Semantic Segmentation in Self-Driving with Discrete Wasserstein Training
However, the cross entropy loss can not take the different importance of each class in an self-driving system into account.
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