Graph Neural Networks Paper List of 2019 Conferences
- 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
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
- 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
- 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
- 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