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07/19/2023
Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation
Modeling customer shopping intentions is a crucial task for e-commerce, ...
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07/07/2023
Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs
Learning on Graphs has attracted immense attention due to its wide real-...
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06/18/2023
In-Process Global Interpretation for Graph Learning via Distribution Matching
Graphs neural networks (GNNs) have emerged as a powerful graph learning ...
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06/02/2023
Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All?
Recent studies on Graph Neural Networks(GNNs) provide both empirical and...
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03/01/2023
Single-Cell Multimodal Prediction via Transformers
The recent development of multimodal single-cell technology has made the...
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02/10/2023
Toward Degree Bias in Embedding-Based Knowledge Graph Completion
A fundamental task for knowledge graphs (KGs) is knowledge graph complet...
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10/17/2022
Test-Time Training for Graph Neural Networks
Graph Neural Networks (GNNs) have made tremendous progress in the graph ...
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10/07/2022
Empowering Graph Representation Learning with Test-Time Graph Transformation
As powerful tools for representation learning on graphs, graph neural ne...
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08/30/2022
Learning Representations for Hyper-Relational Knowledge Graphs
Knowledge graphs (KGs) have gained prominence for their ability to learn...
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06/15/2022
Condensing Graphs via One-Step Gradient Matching
As training deep learning models on large dataset takes a lot of time an...
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06/15/2022
Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective
Recent years have witnessed remarkable success achieved by graph neural ...
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04/27/2022
Identifying Critical LMS Features for Predicting At-risk Students
Learning management systems (LMSs) have become essential in higher educa...
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03/03/2022
Graph Neural Networks for Multimodal Single-Cell Data Integration
Recent advances in multimodal single-cell technologies have enabled simu...
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01/01/2022
Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels
Graph Neural Networks (GNNs) have shown their great ability in modeling ...
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08/12/2021
Graph Trend Networks for Recommendations
Recommender systems aim to provide personalized services to users and ar...
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08/10/2021
Localized Graph Collaborative Filtering
User-item interactions in recommendations can be naturally de-noted as a...
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08/07/2021
Jointly Attacking Graph Neural Network and its Explanations
Graph Neural Networks (GNNs) have boosted the performance for many graph...
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07/05/2021
Elastic Graph Neural Networks
While many existing graph neural networks (GNNs) have been proven to per...
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06/10/2021
Automated Self-Supervised Learning for Graphs
Graph self-supervised learning has gained increasing attention due to it...
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05/10/2021
Graph Feature Gating Networks
Graph neural networks (GNNs) have received tremendous attention due to t...
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05/06/2021
The Authors Matter: Understanding and Mitigating Implicit Bias in Deep Text Classification
It is evident that deep text classification models trained on human data...
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04/21/2021
Improvement of Normal Estimation for PointClouds via Simplifying Surface Fitting
With the burst development of neural networks in recent years, the task ...
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03/30/2021
Fast and Accurate Normal Estimation for Point Cloud via Patch Stitching
This paper presents an effective normal estimation method adopting multi...
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11/19/2020
Node Similarity Preserving Graph Convolutional Networks
Graph Neural Networks (GNNs) have achieved tremendous success in various...
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06/17/2020
Self-supervised Learning on Graphs: Deep Insights and New Direction
The success of deep learning notoriously requires larger amounts of cost...
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05/20/2020
Graph Structure Learning for Robust Graph Neural Networks
Graph Neural Networks (GNNs) are powerful tools in representation learni...
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05/13/2020
DeepRobust: A PyTorch Library for Adversarial Attacks and Defenses
DeepRobust is a PyTorch adversarial learning library which aims to build...
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04/11/2020
A Bayesian Nonparametric Approach for Inferring Drug Combination Effects on Mental Health in People with HIV
Although combination antiretroviral therapy (ART) is highly effective in...
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03/02/2020
Adversarial Attacks and Defenses on Graphs: A Review and Empirical Study
Deep neural networks (DNNs) have achieved significant performance in var...
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01/05/2018
Learning Feature Representations for Keyphrase Extraction
In supervised approaches for keyphrase extraction, a candidate phrase is...
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12/15/2017
