Early-exit GNNs for link prediction move the speed-quality Pareto frontier on the HeaRT benchmark by allowing implicit early exiting without auxiliary losses.
Why should we add early exits to neural networks?Cognitive Computation, 12(5):954–966, September 2020
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A survey that synthesizes dynamic neural network research via a taxonomy of adaptive components and extends the discussion to sensor fusion applications with a supporting repository.
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Early-Exit Graph Neural Networks for Link Prediction
Early-exit GNNs for link prediction move the speed-quality Pareto frontier on the HeaRT benchmark by allowing implicit early exiting without auxiliary losses.
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A Survey on Dynamic Neural Networks: from Computer Vision to Multi-modal Sensor Fusion
A survey that synthesizes dynamic neural network research via a taxonomy of adaptive components and extends the discussion to sensor fusion applications with a supporting repository.