b'Wei Jin'

research

∙ 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, ...

0 Wei Jin, et al. ∙

research

∙ 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-...

0 Zhikai Chen, et al. ∙

research

∙ 06/18/2023

In-Process Global Interpretation for Graph Learning via Distribution Matching

Graphs neural networks (GNNs) have emerged as a powerful graph learning ...

0 Yi Nian, et al. ∙

research

∙ 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...

20 Haitao Mao, et al. ∙

research

∙ 03/01/2023

Single-Cell Multimodal Prediction via Transformers

The recent development of multimodal single-cell technology has made the...

13 Wenzhuo Tang, et al. ∙

research

∙ 02/10/2023

Toward Degree Bias in Embedding-Based Knowledge Graph Completion

A fundamental task for knowledge graphs (KGs) is knowledge graph complet...

6 Harry Shomer, et al. ∙

research

∙ 10/17/2022

Test-Time Training for Graph Neural Networks

Graph Neural Networks (GNNs) have made tremendous progress in the graph ...

3 Yiqi Wang, et al. ∙

research

∙ 10/07/2022

Empowering Graph Representation Learning with Test-Time Graph Transformation

As powerful tools for representation learning on graphs, graph neural ne...

28 Wei Jin, et al. ∙

research

∙ 08/30/2022

Learning Representations for Hyper-Relational Knowledge Graphs

Knowledge graphs (KGs) have gained prominence for their ability to learn...

7 Harry Shomer, et al. ∙

research

∙ 06/15/2022

Condensing Graphs via One-Step Gradient Matching

As training deep learning models on large dataset takes a lot of time an...

12 Wei Jin, et al. ∙

research

∙ 06/15/2022

Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective

Recent years have witnessed remarkable success achieved by graph neural ...

11 Wei Jin, et al. ∙

research

∙ 04/27/2022

Identifying Critical LMS Features for Predicting At-risk Students

Learning management systems (LMSs) have become essential in higher educa...

0 Ying Guo, et al. ∙

research

∙ 03/03/2022

Graph Neural Networks for Multimodal Single-Cell Data Integration

Recent advances in multimodal single-cell technologies have enabled simu...

35 Hongzhi Wen, et al. ∙

research

∙ 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 ...

89 Enyan Dai, et al. ∙

research

∙ 08/12/2021

Graph Trend Networks for Recommendations

Recommender systems aim to provide personalized services to users and ar...

13 Wenqi Fan, et al. ∙

research

∙ 08/10/2021

Localized Graph Collaborative Filtering

User-item interactions in recommendations can be naturally de-noted as a...

12 Yiqi Wang, et al. ∙

research

∙ 08/07/2021

Jointly Attacking Graph Neural Network and its Explanations

Graph Neural Networks (GNNs) have boosted the performance for many graph...

23 Wenqi Fan, et al. ∙

research

∙ 07/05/2021

Elastic Graph Neural Networks

While many existing graph neural networks (GNNs) have been proven to per...

0 Xiaorui Liu, et al. ∙

research

∙ 06/10/2021

Automated Self-Supervised Learning for Graphs

Graph self-supervised learning has gained increasing attention due to it...

10 Wei Jin, et al. ∙

research

∙ 05/10/2021

Graph Feature Gating Networks

Graph neural networks (GNNs) have received tremendous attention due to t...

38 Wei Jin, et al. ∙

research

∙ 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...

11 Haochen Liu, et al. ∙

research

∙ 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 ...

5 Jun Zhou, et al. ∙

research

∙ 03/30/2021

Fast and Accurate Normal Estimation for Point Cloud via Patch Stitching

This paper presents an effective normal estimation method adopting multi...

5 Jun Zhou, et al. ∙

research

∙ 11/19/2020

Node Similarity Preserving Graph Convolutional Networks

Graph Neural Networks (GNNs) have achieved tremendous success in various...

26 Wei Jin, et al. ∙

research

∙ 06/17/2020

Self-supervised Learning on Graphs: Deep Insights and New Direction

The success of deep learning notoriously requires larger amounts of cost...

24 Wei Jin, et al. ∙

research

∙ 05/20/2020

Graph Structure Learning for Robust Graph Neural Networks

Graph Neural Networks (GNNs) are powerful tools in representation learni...

5 Wei Jin, et al. ∙

research

∙ 05/13/2020

DeepRobust: A PyTorch Library for Adversarial Attacks and Defenses

DeepRobust is a PyTorch adversarial learning library which aims to build...

48 Yaxin Li, et al. ∙

research

∙ 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...

0 Wei Jin, et al. ∙

research

∙ 03/02/2020

Adversarial Attacks and Defenses on Graphs: A Review and Empirical Study

Deep neural networks (DNNs) have achieved significant performance in var...

24 Wei Jin, et al. ∙

research

∙ 01/05/2018

Learning Feature Representations for Keyphrase Extraction

In supervised approaches for keyphrase extraction, a candidate phrase is...

0 Corina Florescu, et al. ∙

research

∙ 12/15/2017

A Theoretical Framework for Bayesian Nonparametric Regression: Orthonormal Random Series and Rates of Contraction

We develop a unifying framework for Bayesian nonparametric regression to...

0 Fangzheng Xie, et al. ∙

Wei Jin

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