
Fea2Fea: Exploring Structural Feature Correlations via Graph Neural Networks
Structural features are important features in graph datasets. However, a...
read it

Graph Ensemble Learning over Multiple Dependency Trees for Aspectlevel Sentiment Classification
Recent work on aspectlevel sentiment classification has demonstrated th...
read it

Identityaware Graph Neural Networks
Message passing Graph Neural Networks (GNNs) provide a powerful modeling...
read it

Design Space for Graph Neural Networks
The rapid evolution of Graph Neural Networks (GNNs) has led to a growing...
read it

Direct Multihop Attention based Graph Neural Network
Introducing selfattention mechanism in graph neural networks (GNNs) ach...
read it

Learning to Simulate Complex Physics with Graph Networks
Here we present a general framework for learning simulation, and provide...
read it

Hyperbolic Graph Convolutional Neural Networks
Graph convolutional neural networks (GCNs) embed nodes in a graph into E...
read it

Improving Graph Attention Networks with Large Marginbased Constraints
Graph Attention Networks (GATs) are the stateoftheart neural architec...
read it

Neural Execution of Graph Algorithms
Graph Neural Networks (GNNs) are a powerful representational tool for so...
read it

Positionaware Graph Neural Networks
Learning node embeddings that capture a node's position within the broad...
read it

RedundancyFree Computation Graphs for Graph Neural Networks
Graph Neural Networks (GNNs) are based on repeated aggregations of infor...
read it

GNN Explainer: A Tool for Posthoc Explanation of Graph Neural Networks
Graph Neural Networks (GNNs) are a powerful tool for machine learning on...
read it

Hierarchical Graph Representation Learning with Differentiable Pooling
Recently, graph neural networks (GNNs) have revolutionized the field of ...
read it

Hierarchical Graph Representation Learning withDifferentiable Pooling
Recently, graph neural networks (GNNs) have revolutionized the field of ...
read it

Graph Convolutional Policy Network for GoalDirected Molecular Graph Generation
Generating novel graph structures that optimize given objectives while o...
read it

Graph Convolutional Neural Networks for WebScale Recommender Systems
Recent advancements in deep neural networks for graphstructured data ha...
read it

GraphRNN: A Deep Generative Model for Graphs
Modeling and generating graphs is fundamental for studying networks in b...
read it

Inductive Representation Learning on Large Graphs
Lowdimensional embeddings of nodes in large graphs have proved extremel...
read it
Rex Ying
is this you? claim profile