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Found 4 papers, 3 papers with code
Zero Stability Well Predicts Performance of Convolutional Neural Networks
We first give the interpretation of zero stability in the context of deep learning and then investigate the performance of existing first- and second-order CNNs under different zero-stable circumstances.
Activated Gradients for Deep Neural Networks
The experimental results also demonstrate that the proposed method is able to be adopted in various deep neural networks to improve their performance.
TempNodeEmb:Temporal Node Embedding considering temporal edge influence matrix
As a result, adjacency matrices cannot be directly used by machine learning models for making network or node level predictions.
Self-training semi-supervised classification based on density peaks of data
Having a multitude of unlabeled data and few labeled ones is a common problem in many practical ap- plications.
