b'Suhang Wang'

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 ...

Enyan Dai, et al. ∙

research

∙ 10/15/2021

Label-Wise Message Passing Graph Neural Network on Heterophilic Graphs

Graph Neural Networks (GNNs) have achieved remarkable performance in mod...

Enyan Dai, et al. ∙

research

∙ 08/26/2021

Towards Self-Explainable Graph Neural Network

Graph Neural Networks (GNNs), which generalize the deep neural networks ...

Enyan Dai, 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...

Wenqi Fan, et al. ∙

research

∙ 06/08/2021

Labeled Data Generation with Inexact Supervision

The recent advanced deep learning techniques have shown the promising re...

Enyan Dai, et al. ∙

research

∙ 06/08/2021

NRGNN: Learning a Label Noise-Resistant Graph Neural Network on Sparsely and Noisily Labeled Graphs

Graph Neural Networks (GNNs) have achieved promising results for semi-su...

Enyan Dai, et al. ∙

research

∙ 05/27/2021

Times Series Forecasting for Urban Building Energy Consumption Based on Graph Convolutional Network

The world is increasingly urbanizing and the building industry accounts ...

Yuqing Hu, et al. ∙

research

∙ 04/29/2021

You Can Still Achieve Fairness Without Sensitive Attributes: Exploring Biases in Non-Sensitive Features

Though machine learning models are achieving great success, ex-tensive s...

Tianxiang Zhao, et al. ∙

research

∙ 03/16/2021

Semi-Supervised Graph-to-Graph Translation

Graph translation is very promising research direction and has a wide ra...

Tianxiang Zhao, et al. ∙

research

∙ 03/16/2021

GraphSMOTE: Imbalanced Node Classification on Graphs with Graph Neural Networks

Node classification is an important research topic in graph learning. Gr...

Tianxiang Zhao, et al. ∙

research

∙ 02/20/2021

Spotting Silent Buffer Overflows in Execution Trace through Graph Neural Network Assisted Data Flow Analysis

A software vulnerability could be exploited without any visible symptoms...

Zhilong Wang, et al. ∙

research

∙ 11/23/2020

Explainable Multivariate Time Series Classification: A Deep Neural Network Which Learns To Attend To Important Variables As Well As Informative Time Intervals

Time series data is prevalent in a wide variety of real-world applicatio...

Tsung-Yu Hsieh, et al. ∙

research

∙ 09/03/2020

FairGNN: Eliminating the Discrimination in Graph Neural Networks with Limited Sensitive Attribute Information

Graph neural networks (GNNs) have shown great power in modeling graph st...

Enyan Dai, et al. ∙

research

∙ 09/01/2020

MALCOM: Generating Malicious Comments to Attack Neural Fake News Detection Models

In recent years, the proliferation of so-called "fake news" has caused m...

Thai Le, et al. ∙

research

∙ 06/28/2020

Graph Convolutional Networks against Degree-Related Biases

In recent years, Graph Convolutional Networks (GCNs) show competitive pe...

Xianfeng Tang, 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...

Wei Jin, et al. ∙

research

∙ 06/10/2020

Knowing your FATE: Friendship, Action and Temporal Explanations for User Engagement Prediction on Social Apps

With the rapid growth and prevalence of social network applications (App...

Xianfeng Tang, et al. ∙

research

∙ 05/20/2020

Graph Structure Learning for Robust Graph Neural Networks

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

Wei Jin, et al. ∙

research

∙ 01/27/2020

Ginger Cannot Cure Cancer: Battling Fake Health News with a Comprehensive Data Repository

Nowadays, Internet is a primary source of attaining health information. ...

Enyan Dai, et al. ∙

research

∙ 11/22/2019

Joint Modeling of Local and Global Temporal Dynamics for Multivariate Time Series Forecasting with Missing Values

Multivariate time series (MTS) forecasting is widely used in various dom...

Xianfeng Tang, et al. ∙

research

∙ 11/05/2019

Why X rather than Y? Explaining Neural Model' Predictions by Generating Intervention Counterfactual Samples

Even though the topic of explainable AI/ML is very popular in text and c...

Thai Le, et al. ∙

research

∙ 10/07/2019

Graph Few-shot Learning via Knowledge Transfer

Towards the challenging problem of semi-supervised node classification, ...

Huaxiu Yao, et al. ∙

research

∙ 09/14/2019

Node Injection Attacks on Graphs via Reinforcement Learning

Real-world graph applications, such as advertisements and product recomm...

Yiwei Sun, et al. ∙

research

∙ 08/20/2019

Robust Graph Neural Network Against Poisoning Attacks via Transfer Learning

Graph neural networks (GNNs) are widely used in many applications. Howev...

Xianfeng Tang, et al. ∙

research

∙ 07/06/2019

I Am Not What I Write: Privacy Preserving Text Representation Learning

Online users generate tremendous amounts of textual information by parti...

Ghazaleh Beigi, et al. ∙

research

∙ 06/10/2019

Attacking Graph Convolutional Networks via Rewiring

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

Yao Ma, et al. ∙

research

∙ 04/30/2019

The Role of User Profile for Fake News Detection

Consuming news from social media is becoming increasingly popular. Socia...

Kai Shu, et al. ∙

research

∙ 04/30/2019

Graph Convolutional Networks with EigenPooling

Graph neural networks, which generalize deep neural network models to gr...

Yao Ma, et al. ∙

research

∙ 09/15/2017

Disentangled Variational Auto-Encoder for Semi-supervised Learning

In this paper, we develop a novel approach for semi-supervised VAE witho...

Yang Li, et al. ∙

research

∙ 09/14/2017

Cross-Platform Emoji Interpretation: Analysis, a Solution, and Applications

Most social media platforms are largely based on text, and users often w...

Fred Morstatter, et al. ∙

research

∙ 08/07/2017

Fake News Detection on Social Media: A Data Mining Perspective

Social media for news consumption is a double-edged sword. On the one ha...

Kai Shu, et al. ∙

Suhang Wang

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