2 papers
cs.LG2023
Self-Supervised Siamese Autoencoders
Friederike Baier, Sebastian Mair, Samuel G. Fadel
In contrast to fully-supervised models, self-supervised representation learning only needs a fraction of data to be labeled and often achieves the same or even higher downstream pe…
cs.IR2018
Link Prediction in Dynamic Graphs for Recommendation
Samuel G. Fadel, Ricardo da S. Torres
Recent advances in employing neural networks on graph domains helped push the state of the art in link prediction tasks, particularly in recommendation services. However, the use o…