
BayReL: Bayesian Relational Learning for Multiomics Data Integration
Highthroughput molecular profiling technologies have produced highdime...
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Bayesian Graph Neural Networks with Adaptive Connection Sampling
We propose a unified framework for adaptive connection sampling in graph...
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SemiImplicit Stochastic Recurrent Neural Networks
Stochastic recurrent neural networks with latent random variables of com...
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Temporal Network Sampling
Temporal networks representing a stream of timestamped edges are seeming...
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Variational Graph Recurrent Neural Networks
Representation learning over graph structured data has been mostly studi...
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SemiImplicit Graph Variational AutoEncoders
Semiimplicit graph variational autoencoder (SIGVAE) is proposed to ex...
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Optimizing Consistent Merging and Pruning of Subgraphs in Network Tomography
A communication network can be modeled as a directed connected graph wit...
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Network Shrinkage Estimation
Networks are a natural representation of complex systems across the scie...
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Micro and MacroLevel Churn Analysis of LargeScale Mobile Games
As mobile devices become more and more popular, mobile gaming has emerge...
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Streaming Network Embedding through Local Actions
Recently, considerable research attention has been paid to network embed...
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A SemiSupervised and Inductive Embedding Model for Churn Prediction of LargeScale Mobile Games
Mobile gaming has emerged as a promising market with billiondollar reve...
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Estimating Node Similarity by Sampling Streaming Bipartite Graphs
Bipartite graph data increasingly occurs as a stream of edges that repre...
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Graphlet Decomposition: Framework, Algorithms, and Applications
From social science to biology, numerous applications often rely on grap...
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Nick Duffield
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