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09/20/2023
Towards Data-centric Graph Machine Learning: Review and Outlook
Data-centric AI, with its primary focus on the collection, management, a...
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08/31/2023
Domain-adaptive Message Passing Graph Neural Network
Cross-network node classification (CNNC), which aims to classify nodes i...
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08/18/2023
CARLA: A Self-supervised Contrastive Representation Learning Approach for Time Series Anomaly Detection
We introduce a Self-supervised Contrastive Representation Learning Appro...
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08/10/2023
𝒢^2Pxy: Generative Open-Set Node Classification on Graphs with Proxy Unknowns
Node classification is the task of predicting the labels of unlabeled no...
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07/17/2023
Correlation-aware Spatial-Temporal Graph Learning for Multivariate Time-series Anomaly Detection
Multivariate time-series anomaly detection is critically important in ma...
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07/07/2023
A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection
Time series are the primary data type used to record dynamic system meas...
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06/13/2023
Finding the Missing-half: Graph Complementary Learning for Homophily-prone and Heterophily-prone Graphs
Real-world graphs generally have only one kind of tendency in their conn...
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06/05/2023
Structure-free Graph Condensation: From Large-scale Graphs to Condensed Graph-free Data
Graph condensation, which reduces the size of a large-scale graph by syn...
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06/01/2023
A Survey on Fairness-aware Recommender Systems
As information filtering services, recommender systems have extremely en...
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05/21/2023
Towards Complex Dynamic Physics System Simulation with Graph Neural ODEs
The great learning ability of deep learning models facilitates us to com...
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05/06/2023
A Minimal Approach for Natural Language Action Space in Text-based Games
Text-based games (TGs) are language-based interactive environments for r...
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05/04/2023
Toward the Automated Construction of Probabilistic Knowledge Graphs for the Maritime Domain
International maritime crime is becoming increasingly sophisticated, oft...
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04/17/2023
Normalizing Flow-based Neural Process for Few-Shot Knowledge Graph Completion
Knowledge graphs (KGs), as a structured form of knowledge representation...
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02/23/2023
Auto-HeG: Automated Graph Neural Network on Heterophilic Graphs
Graph neural architecture search (NAS) has gained popularity in automati...
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01/30/2023
On the Interaction between Node Fairness and Edge Privacy in Graph Neural Networks
Due to the emergence of graph neural networks (GNNs) and their widesprea...
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12/22/2022
TxAllo: Dynamic Transaction Allocation in Sharded Blockchain Systems
The scalability problem has been one of the most significant barriers li...
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11/25/2022
Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating
Unsupervised graph representation learning (UGRL) has drawn increasing r...
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11/15/2022
Graph Sequential Neural ODE Process for Link Prediction on Dynamic and Sparse Graphs
Link prediction on dynamic graphs is an important task in graph mining. ...
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11/10/2022
A Comprehensive Survey on Distributed Training of Graph Neural Networks
Graph neural networks (GNNs) have been demonstrated to be a powerful alg...
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11/09/2022
Deep Learning for Time Series Anomaly Detection: A Survey
Time series anomaly detection has applications in a wide range of resear...
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10/30/2022
How Far are We from Robust Long Abstractive Summarization?
Abstractive summarization has made tremendous progress in recent years. ...
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10/17/2022
Unifying Graph Contrastive Learning with Flexible Contextual Scopes
Graph contrastive learning (GCL) has recently emerged as an effective le...
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09/02/2022
Rethinking Efficiency and Redundancy in Training Large-scale Graphs
Large-scale graphs are ubiquitous in real-world scenarios and can be tra...
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08/10/2022
Fast Heterogeneous Federated Learning with Hybrid Client Selection
Client selection schemes are widely adopted to handle the communication-...
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07/06/2022
Simple and Efficient Heterogeneous Graph Neural Network
Heterogeneous graph neural networks (HGNNs) deliver the powerful capabil...
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07/03/2022
An Empirical Survey on Long Document Summarization: Datasets, Models and Metrics
Long documents such as academic articles and business reports have been ...
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06/25/2022
Geometry Contrastive Learning on Heterogeneous Graphs
Self-supervised learning (especially contrastive learning) methods on he...
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06/04/2022
Cross-modal Clinical Graph Transformer for Ophthalmic Report Generation
Automatic generation of ophthalmic reports using data-driven neural netw...
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06/03/2022
Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discrimination
Graph contrastive learning (GCL) alleviates the heavy reliance on label ...
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05/16/2022
Trustworthy Graph Neural Networks: Aspects, Methods and Trends
Graph neural networks (GNNs) have emerged as a series of competent graph...
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04/28/2022
Triformer: Triangular, Variable-Specific Attentions for Long Sequence Multivariate Time Series Forecasting–Full Version
A variety of real-world applications rely on far future information to m...
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03/29/2022
Towards Spatio-Temporal Aware Traffic Time Series Forecasting–Full Version
Traffic time series forecasting is challenging due to complex spatio-tem...
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03/21/2022
Paraphrasing Techniques for Maritime QA system
There has been an increasing interest in incorporating Artificial Intell...
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02/25/2022
Projective Ranking-based GNN Evasion Attacks
Graph neural networks (GNNs) offer promising learning methods for graph-...
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02/25/2022
MAMDR: A Model Agnostic Learning Method for Multi-Domain Recommendation
Large-scale e-commercial platforms in the real-world usually contain var...
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02/17/2022
Multivariate Time Series Forecasting with Dynamic Graph Neural ODEs
Multivariate time series forecasting has long received significant atten...
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02/14/2022
Graph Neural Networks for Graphs with Heterophily: A Survey
Recent years have witnessed fast developments of graph neural networks (...
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02/11/2022
From Unsupervised to Few-shot Graph Anomaly Detection: A Multi-scale Contrastive Learning Approach
Anomaly detection from graph data is an important data mining task in ma...
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02/10/2022
Survey on Graph Neural Network Acceleration: An Algorithmic Perspective
Graph neural networks (GNNs) have been a hot spot of recent research and...
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01/24/2022
Multi-Graph Fusion Networks for Urban Region Embedding
Learning the embeddings for urban regions from human mobility data can r...
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01/19/2022
Dual Space Graph Contrastive Learning
Unsupervised graph representation learning has emerged as a powerful too...
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01/17/2022
Towards Unsupervised Deep Graph Structure Learning
In recent years, graph neural networks (GNNs) have emerged as a successf...
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01/15/2022
Variance-Reduced Heterogeneous Federated Learning via Stratified Client Selection
Client selection strategies are widely adopted to handle the communicati...
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11/25/2021
BaLeNAS: Differentiable Architecture Search via the Bayesian Learning Rule
Differentiable Architecture Search (DARTS) has received massive attentio...
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11/25/2021
Spatio-Temporal Joint Graph Convolutional Networks for Traffic Forecasting
Recent studies focus on formulating the traffic forecasting as a spatio-...
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11/20/2021
Towards Graph Self-Supervised Learning with Contrastive Adjusted Zooming
Graph representation learning (GRL) is critical for graph-structured dat...
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10/17/2021
Adapting Membership Inference Attacks to GNN for Graph Classification: Approaches and Implications
Graph Neural Networks (GNNs) are widely adopted to analyse non-Euclidean...
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10/04/2021
Leveraging Information Bottleneck for Scientific Document Summarization
This paper presents an unsupervised extractive approach to summarize sci...
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09/20/2021
Robust Physical-World Attacks on Face Recognition
Face recognition has been greatly facilitated by the development of deep...
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07/10/2021
