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08/31/2023
Wasserstein Distributionally Robust Chance Constrained Trajectory Optimization for Mobile Robots within Uncertain Safe Corridor
Safe corridor-based Trajectory Optimization (TO) presents an appealing a...
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08/04/2023
VQGraph: Graph Vector-Quantization for Bridging GNNs and MLPs
Graph Neural Networks (GNNs) conduct message passing which aggregates lo...
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07/29/2023
Graph Condensation for Inductive Node Representation Learning
Graph neural networks (GNNs) encounter significant computational challen...
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06/28/2023
Individual and Structural Graph Information Bottlenecks for Out-of-Distribution Generalization
Out-of-distribution (OOD) graph generalization are critical for many rea...
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05/20/2023
Patton: Language Model Pretraining on Text-Rich Networks
A real-world text corpus sometimes comprises not only text documents but...
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04/08/2023
GPT4Rec: A Generative Framework for Personalized Recommendation and User Interests Interpretation
Recent advancements in Natural Language Processing (NLP) have led to the...
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03/07/2023
Fairness-aware Maximal Biclique Enumeration on Bipartite Graphs
Maximal biclique enumeration is a fundamental problem in bipartite graph...
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02/27/2023
Semantic-aware Node Synthesis for Imbalanced Heterogeneous Information Networks
Heterogeneous graph neural networks (HGNNs) have exhibited exceptional e...
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11/01/2022
Efficient Graph Neural Network Inference at Large Scale
Graph neural networks (GNNs) have demonstrated excellent performance in ...
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11/01/2022
Distributed Graph Neural Network Training: A Survey
Graph neural networks (GNNs) are a type of deep learning models that lea...
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09/02/2022
Diffusion Models: A Comprehensive Survey of Methods and Applications
Diffusion models are a class of deep generative models that have shown i...
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06/09/2022
Model Degradation Hinders Deep Graph Neural Networks
Graph Neural Networks (GNNs) have achieved great success in various grap...
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03/02/2022
Information Gain Propagation: a new way to Graph Active Learning with Soft Labels
Graph Neural Networks (GNNs) have achieved great success in various task...
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03/01/2022
Two-Level Supervised Contrastive Learning for Response Selection in Multi-Turn Dialogue
Selecting an appropriate response from many candidates given the utteran...
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12/26/2021
K-Core Decomposition on Super Large Graphs with Limited Resources
K-core decomposition is a commonly used metric to analyze graph structur...
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12/26/2021
Efficient Diversity-Driven Ensemble for Deep Neural Networks
The ensemble of deep neural networks has been shown, both theoretically ...
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10/28/2021
RIM: Reliable Influence-based Active Learning on Graphs
Message passing is the core of most graph models such as Graph Convoluti...
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08/23/2021
Graph Attention Multi-Layer Perceptron
Graph neural networks (GNNs) have recently achieved state-of-the-art per...
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08/02/2021
Evaluating Deep Graph Neural Networks
Graph Neural Networks (GNNs) have already been widely applied in various...
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11/04/2020
