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Found 2 papers, 1 papers with code
Graph-Adaptive Activation Functions for Graph Neural Networks
Activation functions are crucial in graph neural networks (GNNs) as they allow defining a nonlinear family of functions to capture the relationship between the input graph data and their representations.
Multi-label Classification for Automatic Tag Prediction in the Context of Programming Challenges
In this paper, we focus on automating the task of tagging a programming challenge description using machine and deep learning methods.
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