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09/06/2023
Helper Recommendation with seniority control in Online Health Community
Online health communities (OHCs) are forums where patients with similar ...
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09/05/2023
Dynamic Brain Transformer with Multi-level Attention for Functional Brain Network Analysis
Recent neuroimaging studies have highlighted the importance of network-c...
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06/12/2023
Weakly-Supervised Scientific Document Classification via Retrieval-Augmented Multi-Stage Training
Scientific document classification is a critical task for a wide range o...
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06/07/2023
A Survey on Knowledge Graphs for Healthcare: Resources, Applications, and Promises
Healthcare knowledge graphs (HKGs) have emerged as a promising tool for ...
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06/05/2023
Graph-Aware Language Model Pre-Training on a Large Graph Corpus Can Help Multiple Graph Applications
Model pre-training on large text corpora has been demonstrated effective...
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06/05/2023
R-Mixup: Riemannian Mixup for Biological Networks
Biological networks are commonly used in biomedical and healthcare domai...
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06/02/2023
GAD-NR: Graph Anomaly Detection via Neighborhood Reconstruction
Graph Anomaly Detection (GAD) is a technique used to identify abnormal n...
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06/01/2023
PV2TEA: Patching Visual Modality to Textual-Established Information Extraction
Information extraction, e.g., attribute value extraction, has been exten...
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05/30/2023
Beyond One-Model-Fits-All: A Survey of Domain Specialization for Large Language Models
Large language models (LLMs) have significantly advanced the field of na...
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05/06/2023
Transformer-Based Hierarchical Clustering for Brain Network Analysis
Brain networks, graphical models such as those constructed from MRI, hav...
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03/29/2023
When to Pre-Train Graph Neural Networks? An Answer from Data Generation Perspective!
Recently, graph pre-training has attracted wide research attention, whic...
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02/06/2023
MuG: A Multimodal Classification Benchmark on Game Data with Tabular, Textual, and Visual Fields
Multimodal learning has attracted the interest of the machine learning c...
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01/10/2023
Neighborhood-Regularized Self-Training for Learning with Few Labels
Training deep neural networks (DNNs) with limited supervision has been a...
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12/23/2022
Graph Federated Learning with Hidden Representation Sharing
Learning on Graphs (LoG) is widely used in multi-client systems when eac...
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10/13/2022
Brain Network Transformer
Human brains are commonly modeled as networks of Regions of Interest (RO...
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10/10/2022
Towards Training Graph Neural Networks with Node-Level Differential Privacy
Graph Neural Networks (GNNs) have achieved great success in mining graph...
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06/30/2022
Interpretable Graph Neural Networks for Connectome-Based Brain Disorder Analysis
Human brains lie at the core of complex neurobiological systems, where t...
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06/24/2022
Deep Generation of Heterogeneous Networks
Heterogeneous graphs are ubiquitous data structures that can inherently ...
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06/09/2022
Data-Efficient Brain Connectome Analysis via Multi-Task Meta-Learning
Brain networks characterize complex connectivities among brain regions a...
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06/06/2022
A Bird's-Eye Tutorial of Graph Attention Architectures
Graph Neural Networks (GNNs) have shown tremendous strides in performanc...
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05/25/2022
FBNETGEN: Task-aware GNN-based fMRI Analysis via Functional Brain Network Generation
Functional magnetic resonance imaging (fMRI) is one of the most common i...
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05/08/2022
Data-Free Adversarial Knowledge Distillation for Graph Neural Networks
Graph neural networks (GNNs) have been widely used in modeling graph str...
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03/17/2022
Efficient Federated Learning on Knowledge Graphs via Privacy-preserving Relation Embedding Aggregation
Federated Learning (FL) on knowledge graphs (KGs) has yet to be as well ...
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03/17/2022
BrainGB: A Benchmark for Brain Network Analysis with Graph Neural Networks
Mapping the connectome of the human brain using structural or functional...
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02/18/2022
Graph Auto-Encoder Via Neighborhood Wasserstein Reconstruction
Graph neural networks (GNNs) have drawn significant research attention r...
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02/15/2022
Exploiting Data Sparsity in Secure Cross-Platform Social Recommendation
Social recommendation has shown promising improvements over traditional ...
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01/12/2022
How Can Graph Neural Networks Help Document Retrieval: A Case Study on CORD19 with Concept Map Generation
Graph neural networks (GNNs), as a group of powerful tools for represent...
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11/21/2021
Structure-Preserving Graph Kernel for Brain Network Classification
This paper presents a novel graph-based kernel learning approach for con...
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08/31/2021
Structure-Aware Hard Negative Mining for Heterogeneous Graph Contrastive Learning
Recently, heterogeneous Graph Neural Networks (GNNs) have become a de fa...
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07/23/2021
Effective and Interpretable fMRI Analysis via Functional Brain Network Generation
Recent studies in neuroscience show great potential of functional brain ...
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07/11/2021
BrainNNExplainer: An Interpretable Graph Neural Network Framework for Brain Network based Disease Analysis
Interpretable brain network models for disease prediction are of great v...
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07/11/2021
Zero-Shot Scene Graph Relation Prediction through Commonsense Knowledge Integration
Relation prediction among entities in images is an important step in sce...
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07/07/2021
Joint Embedding of Structural and Functional Brain Networks with Graph Neural Networks for Mental Illness Diagnosis
Multimodal brain networks characterize complex connectivities among diff...
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07/03/2021
On Positional and Structural Node Features for Graph Neural Networks on Non-attributed Graphs
Graph neural networks (GNNs) have been widely used in various graph-rela...
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06/25/2021
Subgraph Federated Learning with Missing Neighbor Generation
Graphs have been widely used in data mining and machine learning due to ...
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06/25/2021
Federated Graph Classification over Non-IID Graphs
Federated learning has emerged as an important paradigm for training mac...
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05/31/2021
Controllable Gradient Item Retrieval
In this paper, we identify and study an important problem of gradient it...
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05/07/2021
Graph Entropy Guided Node Embedding Dimension Selection for Graph Neural Networks
Graph representation learning has achieved great success in many areas, ...
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03/27/2021
Multi-Facet Recommender Networks with Spherical Optimization
Implicit feedback is widely explored by modern recommender systems. Sinc...
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09/11/2020
Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization
Graph neural networks (GNNs) have been shown with superior performance i...
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07/06/2020
GCN for HIN via Implicit Utilization of Attention and Meta-paths
Heterogeneous information network (HIN) embedding, aiming to map the str...
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06/07/2020
Unsupervised Differentiable Multi-aspect Network Embedding
Network embedding is an influential graph mining technique for represent...
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05/01/2020
Secure Network Release with Link Privacy
Many data mining and analytical tasks rely on the abstraction of network...
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04/01/2020
Heterogeneous Network Representation Learning: Survey, Benchmark, Evaluation, and Beyond
Since real-world objects and their interactions are often multi-modal an...
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09/29/2019
I Know You'll Be Back: Interpretable New User Clustering and Churn Prediction on a Mobile Social Application
As online platforms are striving to get more users, a critical challenge...
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09/29/2019
Query-Specific Knowledge Summarization with Entity Evolutionary Networks
Given a query, unlike traditional IR that finds relevant documents or en...
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09/29/2019
Neural Embedding Propagation on Heterogeneous Networks
Classification is one of the most important problems in machine learning...
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09/29/2019
Meta-Graph Based HIN Spectral Embedding: Methods, Analyses, and Insights
In this work, we propose to study the utility of different meta-graphs, ...
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08/04/2019
GraphBLAST: A High-Performance Linear Algebra-based Graph Framework on the GPU
High-performance implementations of graph algorithms are challenging to ...
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11/28/2018
