- Abnormal Event Detection via Heterogeneous Information Network Embedding
- Cash-out User Detection based on Attributed Heterogeneous Information Network with a Hierarchical Attention Mechanism
- Hyperbolic Heterogeneous Information Network Embedding
- Tri-Party Deep Network Representation
- Dynamic Network Embedding: An Extended Approach for Skip-gram based Network Embedding
- ActiveHNE: Active Heterogeneous Network Embedding
- Active Discriminative Network Representation Learning
- Variational Graph Embedding and Clustering with Laplacian Eigenmaps
- Joint Link Prediction and Network Alignment via Cross-graph Embedding
- SPINE: Structural Identity Preserved Inductive Network Embedding
- Network Embedding under Partial Monitoring for Evolving Networks
- Adversarially Regularized Graph Autoencoder for Graph Embedding
- Network-Specific Variational Auto-Encoder for Embedding in Attribute Networks
- Feature Hashing for Network Representation Learning
- Efficient Attributed Network Embedding via Recursive Randomized Hashing
- Hierarchical Representation Learning for Bipartite Graphs
- Learning Network Embedding with Community Structural Information
- Graph and Autoencoder Based Feature Extraction for Zero-shot Learning
- ANRL: Attributed Network Representation Learning via Deep Neural Networks
- Exploiting Interaction Links for Node Classification with Deep Graph Neural Networks
- Deep Attributed Network Embedding
- Integrative Network Embedding via Deep Joint Reconstruction
- Discrete Network Embedding
- Adversarial Graph Embedding for Ensemble Clustering
- Unified Embedding Model over Heterogeneous Information Network for Personalized Recommendation
- MASTER: across Multiple social networks, integrate Attribute and STructure Embedding for Reconciliation
- Node Embedding over Temporal Graphs
- Network Embedding with Dual Generation Tasks
- Triplet Enhanced AutoEncoder: Model-free Discriminative Network Embedding
- DeepWalk: Online Learning of Social Representations
- LINE: Large-scale Information Network Embedding
- PTE: Predictive Text Embedding through Large-scale Heterogeneous Text Networks
- Semi-Supervised Classification with Graph Convolutional Networks
- Task-Guided and Path-Augmented Heterogeneous Network Embedding for Author Identification
- Name Disambiguation in Anonymized Graphs using Network Embedding
- Semi-supervised Embedding in Attributed Networks with Outliers
- struc2vec: Learning Node Representations from Structural Identity
- Graph Embedding Techniques, Applications, and Performance: A Survey
- Attributed Network Embedding for Learning in a Dynamic Environment
- Inductive Representation Learning on Large Graphs
- HARP: Hierarchical Representation Learning for Networks
- Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking
- Representation Learning on Graphs: Methods and Applications
- An Attention-based Collaboration Framework for Multi-View Network Representation Learning
- A Comprehensive Survey of Graph Embedding: Problems, Techniques and Applications
- Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec
- Learning Graph Representations with Embedding Propagation
- Learning Structural Node Embeddings via Diffusion Wavelets
- Stochastic Training of Graph Convolutional Networks with Variance Reduction
- Graph Attention Networks
- Adversarial Network Embedding
- GraphGAN: Graph Representation Learning with Generative Adversarial Nets
- TIMERS: Error-Bounded SVD Restart on Dynamic Networks
- Structural Deep Embedding for Hyper-Networks
- Representation Learning for Scale-free Networks
- SHINE: Signed Heterogeneous Information Network Embedding for Sentiment Link Prediction
- Network Representation Learning: A Survey
- FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling
- REGAL: Representation Learning-based Graph Alignment
- Out-of-sample extension of graph adjacency spectral embedding
- MILE: A Multi-Level Framework for Scalable Graph Embedding
- NetGAN: Generating Graphs via RandomWalks
- Semi-supervised User Geolocation via Graph Convolutional Networks
- AnonymousWalk Embeddings
- MolGAN: An implicit generative model for small molecular graphs
- Relational inductive bias for physical construction in humans and machines
- Graph Networks as Learnable Physics Engines for Inference and Control
- Relational inductive biases, deep learning, and graph networks
- Relational recurrent neural networks
- Graph Convolutional Neural Networks forWeb-Scale Recommender Systems
- A Tutorial on Network Embeddings
- Large-Scale Learnable Graph Convolutional Networks
- Enhanced Network Embeddings via Exploiting Edge Labels
- Latent Network Summarization: Bridging Network Embedding and Summarization
- Neural IR Meets Graph Embedding: A Ranking Model for Product Search
- Collaborative Similarity Embedding for Recommender Systems
- Interaction Embeddings for Prediction and Explanation in Knowledge Graphs
- Dual Graph Attention Networks for Deep Latent Representation of Multifaceted Social Effects in Recommender Systems
- DDGK: Learning Graph Representations for Deep Divergence Graph Kernels
- Tag2Vec: Learning Tag Representations in Tag Networks
- Is a Single Vector Enough? Exploring Node Polysemy for Network Embedding
- Deep Bayesian Optimization on Attributed Graphs
- Adversarial Training Methods for Network Embedding
- HIN2Vec: Explore Meta-paths in Heterogeneous Information Networks for Representation Learning
- NetWalk: A Flexible Deep Embedding Approach for Anomaly Detection in Dynamic Networks
- Scalable Multiplex Network Embedding
- Personalized Question Routing via Heterogeneous Network Embedding
- Your Style Your Identity: LeveragingWriting and Photography Styles for Drug Trafficker Identification in Darknet Markets over Attributed Heterogeneous Information Network
- Self-Paced Network Embedding
- Multi-facet Network Embedding: Beyond the General Solution of Detection and Representa
- Community Detection in Attributed Graphs: An Embedding Approach
- Bernoulli Embeddings for Graphs
- Building Causal Graphs from Medical Literature and Electronic Medical Records
- Spectral Clustering in Heterogeneous Information Networks
- MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing
- CANE: Context-Aware Network Embedding for Relation Modeling
- Adversarial Attacks on Node Embeddings via Graph Poisoning
- Compositional Fairness Constraints for Graph Embeddings
- Learning Node Embeddings in Interaction Graphs
- On Embedding Uncertain Graphs
- Multi-view Clustering with Graph Embedding for Connectome Analysis
- Learning Community Embedding with Community Detection and Node Embedding on Graphs
- DepthLGP: Learning Embeddings of Out-of-Sample Nodes in Dynamic Networks
- metapath2vec: Scalable Representation Learning for Heterogeneous Networks
- GraRep: Learning Graph Representations with Global Structural Information
- Dynamic Network Embedding by Modeling Triadic Closure Process
- Graph U-Nets
- GraphZoom: A multi-level spectral approach for accurate and scalable graph embedding
- Asymmetric Transitivity Preserving Graph Embedding
- Embedding Temporal Network via Neighborhood Formation
- Are Meta-Paths Necessary? Revisiting Heterogeneous Graph Embeddings
- Network Representation Learning with Rich Text Information
- Fairwalk: Towards Fair Graph Embedding
- Max-Margin DeepWalk: Discriminative Learning of Network Representation
- Fast Network Embedding Enhancement via High Order Proximity Approximation
- TransNet: Translation-Based Network Representation Learning for Social Relation Extraction
- Inductive and Unsupervised Representation Learning on Graph Structured Objects
- Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks
- Easing Embedding Learning by Comprehensive Transcription of Heterogeneous Information Networks
- Learning Deep Network Representations with Adversarially Regularized Autoencoders
- Non-transitive Hashing with Latent Similarity Components
- Re-evaluating Embedding-Based Knowledge Graph Completion Methods
- Self-Attention Graph Pooling
- Graph Matching Networks for Learning the Similarity of Graph Structured Objects
- Low-dimensional statistical manifold embedding of directed graphs
- Disentangled Graph Convolutional Networks
- Stochastic Blockmodels meet Graph Neural Networks
- Multi-Dimensional Network Embedding with Hierarchical Structure
- Improve Network Embeddings with Regularization
- Arbitrary-Order Proximity Preserved Network Embedding
- Community Preserving Network Embedding
- Deep Variational Network Embedding in Wasserstein Space
- Incorporating Network Embedding into Markov Random Field for Better Community Detection
- Deep Recursive Network Embedding with Regular Equivalence
- Scalable Optimization for Embedding Highly-Dynamic and Recency-Sensitive Data
- Hierarchical Taxonomy Aware Network Embedding
- N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules
- Dynamic Embeddings for User Profiling in Twitter
- Structural Neighborhood Based Classification of Nodes in a Network
- GMNN: Graph Markov Neural Networks
- RaRE: Social Rank Regulated Large-scale Network Embedding
- node2vec: Scalable Feature Learning for Networks
- Deep Inductive Network Representation Learning
- Structural Deep Network Embedding
- SIDE: Representation Learning in Signed Directed Networks
- Attributed Signed Network Embedding
- Network Embedding with Completely-imbalanced Labels
- Co-embedding Attributed Networks
- Learning Latent Representations of Nodes for Classifying in Heterogeneous Social Networks
- Simplifying Graph Convolutional Networks
- Co-Regularized Deep Multi-Network Embedding
- Gromov-Wasserstein Learning for Graph Matching and Node Embedding
- Revisiting Semi-Supervised Learning with Graph Embeddings
- Position-aware Graph Neural Networks
eftekharulislam30 / network-representation-learning-papers Goto Github PK
View Code? Open in Web Editor NEWThis project forked from manjunath5496/network-representation-learning-papers
"Most of us must learn to love people and use things rather than loving things and using people."― Roy T. Bennett