2019-GraphNeuralNetworksPaperList

Graph Neural Networks Paper List of 2019 Conferences

• ICML | 2019
• ICLR | 2019
• AAAI | 2019
• IJCAI | 2019
• Aistats | 2019

ICML | 2019

• Adversarial Attacks on Node Embeddings via Graph Poisoning
• TibGM: A Transferable and Information-Based Graphical Model Approach for Reinforcement Learning
• Molecular Hypergraph Grammar with Its Application to Molecular Optimization
• GMNN: Graph Markov Neural Networks
• Graph Neural Network for Music Score Data and Modeling Expressive Piano Performance
• Self-Attention Graph Pooling
• Circuit-GNN: Graph Neural Networks for Distributed Circuit Design
• Lexicographic and Depth-Sensitive Margins in Homogeneous and Non-Homogeneous Deep Models
• Optimal Transport for structured data with application on graphs
• A Persistent Weisfeiler--Lehman Procedure for Graph Classification
• Improved Dynamic Graph Learning through Fault-Tolerant Sparsification
• Graph Matching Networks for Learning the Similarity of Graph Structured Objects
• Graphical-model based estimation and inference for differential privacy
• Graph U-Nets
• Bayesian Joint Spike-and-Slab Graphical Lasso
• Fast Incremental von Neumann Graph Entropy Computation: Theory, Algorithm, and Applications
• GEOMetrics: Exploiting Geometric Structure for Graph-Encoded Objects
• Simplifying Graph Convolutional Networks
• Graph Convolutional Gaussian Processes
• Graph Element Networks: adaptive, structured computation and memory
• A Baseline for Any Order Gradient Estimation in Stochastic Computation Graphs
• Position-aware Graph Neural Networks
• Tensor Variable Elimination for Plated Factor Graphs
• Discriminative Regularization for Latent Variable Models with Applications to Electrocardiography
• Relational Pooling for Graph Representations
• Disentangled Graph Convolutional Networks
• Learning to Route in Similarity Graphs
• Active Learning with Disagreement Graphs
• Open Vocabulary Learning on Source Code with a Graph-Structured Cache
• Learning Discrete Structures for Graph Neural Networks
• MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing
• Compositional Fairness Constraints for Graph Embeddings
• Stochastic Blockmodels meet Graph Neural Networks
• Stochastic Iterative Hard Thresholding for Graph-structured Sparsity Optimization
• Online Learning with Sleeping Experts and Feedback Graphs
• Graphite: Iterative Generative Modeling of Graphs
• Tight Kernel Query Complexity of Kernel Ridge Regression and Kernel
• Learning to Exploit Long-term Relational Dependencies in Knowledge Graphs
• Dimensionality Reduction for Tukey Regression
• Efficient Full-Matrix Adaptive Regularization
• Gromov-Wasserstein Learning for Graph Matching and Node Embedding
• Spectral Clustering of Signed Graphs via Matrix Power Means
• Breaking the gridlock in Mixture-of-Experts: Consistent and Efficient Algorithms
• Efficient Nonconvex Regularized Tensor Completion with Structure-aware Proximal Iterations
• Geometric Scattering for Graph Data Analysis
• Graph Resistance and Learning from Pairwise Comparisons
• Robust Estimation of Tree Structured Gaussian Graphical Models
• Spectral Approximate Inference
• Partially Linear Additive Gaussian Graphical Models
• DAG-GNN: DAG Structure Learning with Graph Neural Networks
• Random Walks on Hypergraphs with Edge-Dependent Vertex Weights
• Distributed, Egocentric Representations of Graphs for Detecting Critical Structures
• Hyperbolic Disk Embeddings for Directed Acyclic Graphs
• Learning and Reasoning with Graph-Structured Representations

ICLR | 2019

Representation Learning on Graphs and Manifolds[workshop: https://rlgm.github.io/papers/]

• How Powerful are Graph Neural Networks?
• LanczosNet: Multi-Scale Deep Graph Convolutional Networks
• Diffusion Scattering Transforms on Graphs
• Learning Localized Generative Models for 3D Point Clouds via Graph Convolution
• Predict then Propagate: Graph Neural Networks meet Personalized PageRank
• Generative Code Modeling with Graphs
• Graph Wavelet Neural Network
• Capsule Graph Neural Network
• Building Dynamic Knowledge Graphs from Text using Machine Reading Comprehension
• Large Scale Graph Learning From Smooth Signals
• Supervised Community Detection with Line Graph Neural Networks
• Adversarial Attacks on Graph Neural Networks via Meta Learning
• RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space
• Invariant and Equivariant Graph Networks
• Dynamic Sparse Graph for Efficient Deep Learning
• Deep Graph Infomax
• Graph HyperNetworks for Neural Architecture Search
• LayoutGAN: Generating Graphic Layouts with Wireframe Discriminators
• DyRep: Learning Representations over Dynamic Graphs
• Neural Graph Evolution: Automatic Robot Design
• Learning Multimodal Graph-to-Graph Translation for Molecule Optimization

AAAI | 2019

• Embedding Uncertain Knowledge Graphs
• TransGate: Knowledge Graph Embedding with Shared Gate Structure
• Spatiotemporal Multi-Graph Convolution Network for Ride-hailing Demand Forecasting
• Cross-domain Visual Representations via Unsupervised Graph Alignment
• Deep Bayesian Optimization on Attributed Graphs
• GAMENet: Graph Augmented MEmory Networks for Recommending Medication
• GeniePath: Graph Neural Networks with Adaptive Receptive Paths
• Hypergraph Neural Networks
• Graph Convolutional Networks for Text Classification
• Visual-semantic Graph Reasoning for Pedestrian Attribute Recognition
• Logic Attention Based Neighborhood Aggregation for Inductive Knowledge Graph
• Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow
• I Know the Relationships: Zero-Shot Action Recognition via Two-Stream Graph Convolutional Networks and Knowledge Graphs
• On Completing Sparse Knowledge Graph with Transitive Relation Embedding
• Learning Non-Uniform Hypergraph for Multi-Object Tracking
• Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks
• Building Causal Graphs from Medical Literature and Electronic Medical Records
• ATP: Directed Graph Embedding with Asymmetric Transitivity Preservation
• Dynamic Spatial-Temporal Graph Convolutional Neural Networks for Traffic Forecasting
• Congestion Graphs for Automated Time Predictions
• Compiling Bayesian Network Classifiers into Decision Graphs
• Neural Collective Graphical Models for Estimating Spatio-temporal Population Flow from Aggregated Data
• Markov Random Field meets Graph Convolutional Network: End-to-End Learning for Semi-Supervised Community Detection
• Incorporating Semantic Similarity with Geographic Correlation for Query-POI Relevance Learning
• Multi-CGN: Graph Convolutional Networks for Multi-View Networks, with Applications to Global Poverty
• Deep Hierarchical Graph Convolution for Election Prediction from Geospatial Census Data
• Validation of Growing Knowledge Graphs by Abductive Text Evidences
• Entity Alignment between Knowledge Graphs Using Attribute Embeddings
• Learning to Solve NP-Complete Problems -- A Graph Neural Network for the Decision TSP
• Hypergraph Optimization for Multi-structural Geometric Model Fitting
• Understanding Pictograph with Facial Features: End-to-End Sentence-level Lip Reading of Chinese
• Sliding Window Temporal Graph Coloring
• Counting and Sampling Markov Equivalent Directed Acyclic Graphs
• Graph CNNs with Motif and Variable Temporal Block for Skeleton-based Action Recognition
• Communication-optimal distributed dynamic graph clustering
• Designing Deep Generative Models for Molecular Graphs
• Fast Relational Probabilistic Inference and Learning: Approximate Counting via Hypergraphs
• Bayesian Graph Convolutional Neural Networks for Semi-supervised Classification
• An Open-World Extension to Knowledge Graph Completion Models
• Analysis of Joint Multilingual Sentence Representations and Semantic K-Nearest Neighbor Graphs
• CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison
• Graph based Translation Memory for Neural Machine Translation
• Improved Knowledge Graph Embedding using Background Taxonomic Information
• ACM: Adaptive Cross-Modal Graph Convolutional Neural Networks for RGB-D Scene Recognition
• Uncovering Specific-Shape Graph Anomalies in Attributed Graphs
• Reasoning over Knowledge Graph Paths for Recommendation
• Spatio-Temporal Graph Routing for Skeleton-based Action Recognition
• Minimum Intervention Cover of a Causal Graph
• Modelling Autobiographical Memory Loss Across Life Span
• Wasserstein Soft Label Propagation on Hypergraphs: Algorithm and Generalization Error Bounds
• Matrix Completion for Graph-Based Deep Semi-Supervised Learning
• Ladder Gamma Variational Autoencoders for Graphs
• Session-based Recommendation with Graph Neural Network
• Geometric Hawkes Processes with Graph Convolutional Recurrent Neural Networks
• Gaussian-Induced Convolution for Graphs

IJCAI | 2019

• 3DViewGraph: Learning Global Features for 3D Shapes from A Graph of Unordered Views with Attention:
• A Degeneracy Framework for Scalable Graph Autoencoders
• A Vectorized Relational Graph Convolutional Network for Multi-Relational Network Alignment
• AddGraph: Anomaly Detection in Dynamic Graph using Attention-based Temporal GCN
• Adversarial Examples for Graph Data: Deep Insights into Attack and Defense
• Adversarial Graph Embedding for Ensemble Clustering
• An End-to-End Community Detection Model: Integrating LDA into Markov Random Field via Factor Graph
• Anytime Bottom-Up Rule Learning for Knowledge Graph Completion
• Attributed Graph Clustering via Adaptive Graph Convolution
• Attributed Graph Clustering: A Deep Attentional Embedding Approach
• Binarized Collaborative Filtering with Distilling Graph Convolutional Network
• CensNet: Convolution with Edge-Node Switching in Graph Neural Networks
• Crafting Efficient Neural Graph of Large Entropy
• Cutset Bayesian Networks: A New Representation for Learning Rao-Blackwellised Graphical Models
• Data Poisoning Attack against Knowledge Graph Embedding
• Diffusion and Auction on Graphs
• Dual Self-Paced Graph Convolutional Network: Towards Reducing Attribute Distortions Induced by Topology
• Dynamic Electronic Toll Collection via Multi-Agent Deep Reinforcement Learning with Edge-Based Graph Convolutional Network Representation
• Dynamic Hypergraph Neural Networks
• Efficient Regularization Parameter Selection for Latent Variable Graphical Models via Bi-Level Optimization
• Exploiting Interaction Links for Node Classification with Deep Graph Neural Networks
• Fairwalk: Towards Fair Graph Embedding
• Fast Algorithm for K-Truss Discovery on Public-Private Graphs
• Fine-grained Event Categorization with Heterogeneous Graph Convolutional Networks
• GCN-LASE: Towards Adequately Incorporating Link Attributes in Graph Convolutional Networks
• Geo-ALM: POI Recommendation by Fusing Geographical Information and Adversarial Learning Mechanism
• Graph and Autoencoder Based Feature Extraction for Zero-shot Learning
• Graph Contextualized Self-Attention Network for Session-based Recommendation
• Graph Convolutional Network Hashing for Cross-Modal Retrieval
• Graph Convolutional Networks on User Mobility Heterogeneous Graphs for Social Relationship Inference:
• Graph Convolutional Networks using Heat Kernel for Semi-supervised Learning
• Graph Mining Meets Crowdsourcing: Extracting Experts for Answer Aggregation
• Graph Space Embedding
• Graph WaveNet for Deep Spatial-Temporal Graph Modeling
• Graph-based Neural Sentence Ordering
• Graphical One-Sided Markets
• GSN: A Graph-Structured Network for Multi-Party Dialogues
• Heterogeneous Graph Matching Networks for Unknown Malware Detection
• Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification
• Hierarchical Representation Learning for Bipartite Graphs
• Hypergraph Induced Convolutional Manifold Networks
• Joint Link Prediction and Network Alignment via Cross-graph Embedding
• Large Scale Evolving Graphs with Burst Detection
• Learning Image-Specific Attributes by Hyperbolic Neighborhood Graph Propagation
• Learning Shared Vertex Representation in Heterogeneous Graphs with Convolutional Networks for Recommendation
• Masked Graph Convolutional Network
• MR-GNN: Multi-Resolution and Dual Graph Neural Network for Predicting Structured Entity Interactions
• Multi-view Knowledge Graph Embedding for Entity Alignment:
• Neighborhood-Aware Attentional Representation for Multilingual Knowledge Graphs
• Node Embedding over Temporal Graphs
• Non-smooth Optimization over Stiefel Manifolds with Applications to Dimensionality Reduction and Graph Clustering
• Out-of-sample Node Representation Learning for Heterogeneous Graph in Real-time Android Malware Detection
• Path extrapolation using Graph Neural Networks
• Prototype Propagation Networks (PPN) for Weakly-supervised Few-shot Learning on Category Graph
• Regarding Jump Point Search and Subgoal Graphs
• Relation-Aware Entity Alignment for Heterogeneous Knowledge Graphs
• Scaling Fine-grained Modularity Clustering for Massive Graphs
• Schelling Games on Graphs
• Semi-supervised User Profiling with Heterogeneous Graph Attention Networks
• Solving the Satisfiability Problem of Modal Logic S5 Guided by Graph Coloring
• SPAGAN: Shortest Path Graph Attention Network
• Spatio-Temporal Attentive RNN for Node Classification in Temporal Attributed Graphs
• STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender Systems
• STG2Seq: Spatial-Temporal Graph to Sequence Model for Multi-step Passenger Demand Forecasting
• Topology Attack and Defense for Graph Neural Networks
• Topology Optimization based Graph Convolutional Network
• TransMS: Knowledge Graph Embedding for Complex Relations by Multidirectional Semantics:
• Tree Sampling Divergence: An Information-Theoretic Metric for Hierarchical Graph Clustering
• Unsupervised Embedding Enhancements of Knowledge Graphs using Textual Associations
• Unsupervised Inductive Graph-Level Representation Learning via Graph-Graph Proximity
• Variational Graph Embedding and Clustering with Laplacian Eigenmaps
• MINA: Multilevel Knowledge-Guided Attention for Modeling Electrocardiography Signals
• Pretraining of Graph Augmented Transformers for Medication Recommendation
• Risk Assessment for Networked-guarantee Loans Using High-order Graph Attention Representation
• A Refined Understanding of Cost-optimal Planning with Polytree Causal Graphs
• Adversarial Attacks on Neural Networks for Graph Data
• OpenMarkov, an open-source tool for probabilistic graphical models

Aistats | 2019

• Identifiability of Generalized Hypergeometric Distribution (GHD) Directed Acyclic Graphical Models
• Modularity-based Sparse Soft Graph Clustering
• Graph Embedding with Shifted Inner Product Similarity and Its Improved Approximation Capability
• High-dimensional Mixed Graphical Model with Ordinal Data: Parameter Estimation and Statistical Inference
• Robust Graph Embedding with Noisy Link Weights
• A Bayesian model for sparse graphs with flexible degree distribution and overlapping community structure
• Finding the bandit in a graph: Sequential search-and-stop
• Confidence-based Graph Convolutional Networks for Semi-Supervised Learning
• Amortized Variational Inference with Graph Convolutional Networks for Gaussian Processes
• Online learning with feedback graphs and switching costs
• Active learning over hypergraphs with pointwise and pairwise queries
• Credit Assignment Techniques in Stochastic Computation Graphs
• Adaptive Rao-Blackwellisation in Gibbs Sampling for Probabilistic Graphical Models
• Graph to Graph: a Topology Aware Approach for Graph Structures Learning and Generation
• Improved Semi-Supervised Learning with Multiple Graphs
• Sample Efficient Graph-Based Optimization with Noisy Observations
• Representation Learning on Graphs: A Reinforcement Learning Application