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Found 7 papers, 2 papers with code
Differentiable and Scalable Generative Adversarial Models for Data Imputation
DIM leverages a new masking Sinkhorn divergence function to make an arbitrary generative adversarial imputation model differentiable, while for such a differentiable imputation model, SSE can estimate an appropriate sample size to ensure the user-specified imputation accuracy of the final model.
Generative Semi-supervised Learning for Multivariate Time Series Imputation
In this paper, we propose a novel semi-supervised generative adversarial network model, named SSGAN, for missing value imputation in multivariate time series data.
Generative Adversarial Network
Multivariate Time Series Imputation
+2
N2VSCDNNR: A Local Recommender System Based on Node2vec and Rich Information Network
In particular, we use a bipartite network to construct the user-item network, and represent the interactions among users (or items) by the corresponding one-mode projection network.
Can Adversarial Network Attack be Defended?
In this paper, we are interested in the possibility of defense against adversarial attack on network, and propose defense strategies for GNNs against attacks.
Social and Information Networks Physics and Society
GC-LSTM: Graph Convolution Embedded LSTM for Dynamic Link Prediction
To the best of our knowledge, it is the first time that GCN embedded LSTM is put forward for link prediction of dynamic networks.
Social and Information Networks Physics and Society
Link Prediction Adversarial Attack
Deep neural network has shown remarkable performance in solving computer vision and some graph evolved tasks, such as node classification and link prediction.
Physics and Society Social and Information Networks
Fast Gradient Attack on Network Embedding
Network embedding maps a network into a low-dimensional Euclidean space, and thus facilitate many network analysis tasks, such as node classification, link prediction and community detection etc, by utilizing machine learning methods.
Physics and Society Social and Information Networks
