Link Prediction Without Learning
… and propose to solve link prediction tasks by enhancing … GNNs may not be required for
link prediction tasks, and that … We introduce a non-neural baseline model for link prediction …
link prediction tasks, and that … We introduce a non-neural baseline model for link prediction …
Link prediction based on graph neural networks
… It is also interesting that compared to SEAL without node2vec embeddings (Table 1), joint
learning does not always improve the performance. More experiments and discussion are …
learning does not always improve the performance. More experiments and discussion are …
A deep learning approach to link prediction in dynamic networks
… in exponential family for link prediction in dynamic networks. The … prediction phase to O(n)
without reducing model capacity. … – ctRBM for dynamic link prediction. The proposed model suc…
without reducing model capacity. … – ctRBM for dynamic link prediction. The proposed model suc…
Link prediction with non-contrastive learning
… To emulate the effect of negative sampling without actually performing it, we propose
Triplet-BGRL (T-BGRL). In addition to the two augmentations performed during standard non-…
Triplet-BGRL (T-BGRL). In addition to the two augmentations performed during standard non-…
[PDF][PDF] Link prediction using supervised learning
… Link prediction is a key research direction within this area. In this paper, we study link prediction
as a supervised learning … to the performance under the supervised learning setup. The …
as a supervised learning … to the performance under the supervised learning setup. The …
Learning spectral graph transformations for link prediction
J Kunegis, A Lommatzsch - … Conference on Machine Learning, 2009 - dl.acm.org
… We present a unified framework for learning link prediction and … We show how the parameters
of these prediction functions can … can be made about them without having to evaluate each …
of these prediction functions can … can be made about them without having to evaluate each …
New perspectives and methods in link prediction
RN Lichtenwalter, JT Lussier, NV Chawla - Proceedings of the 16th ACM …, 2010 - dl.acm.org
… of class imbalance specific to the task of link prediction. … vised learning, we cast link
prediction as a problem in class … methods, but that we do so without using them as features, we …
prediction as a problem in class … methods, but that we do so without using them as features, we …
Coupledlp: Link prediction in coupled networks
… Permission to make digital or hard copies of all or part of this work for personal or classroom
use is granted without … Link prediction using supervised learning. In SDM’06 workshop on …
use is granted without … Link prediction using supervised learning. In SDM’06 workshop on …
Learning to extrapolate knowledge: Transductive few-shot out-of-graph link prediction
… framework that embeds unseen entities without additional re-training, we compare GENs
against models trained from scratch including unseen entities, for 3-shot OOG …
against models trained from scratch including unseen entities, for 3-shot OOG …
A survey of link prediction in complex networks
… Permission to make digital or hard copies of part or all of this work for personal or classroom
use is granted without fee provided that copies are not made or distributed for profit or …
use is granted without fee provided that copies are not made or distributed for profit or …
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