b'Xiao Huang'

research

∙ 07/22/2023

Collaborative Graph Neural Networks for Attributed Network Embedding

Graph neural networks (GNNs) have shown prominent performance on attribu...

0 Qiaoyu Tan, et al. ∙

research

∙ 06/29/2023

Towards Personalized Cold-Start Recommendation with Prompts

Recommender systems play a crucial role in helping users discover inform...

0 Xuansheng Wu, et al. ∙

research

∙ 05/31/2023

DeepMerge: Deep Learning-Based Region-Merging for Image Segmentation

Accurate segmentation of large areas from very high spatial-resolution (...

0 Xianwei Lv, et al. ∙

research

∙ 04/29/2023

Beyond Prediction: On-street Parking Recommendation using Heterogeneous Graph-based List-wise Ranking

To provide real-time parking information, existing studies focus on pred...

0 Hanyu Sun, et al. ∙

research

∙ 01/30/2023

Coarse-to-fine Hybrid 3D Mapping System with Co-calibrated Omnidirectional Camera and Non-repetitive LiDAR

This paper presents a novel 3D mapping robot with an omnidirectional fie...

0 Ziliang Miao, et al. ∙

research

∙ 12/20/2022

MolCPT: Molecule Continuous Prompt Tuning to Generalize Molecular Representation Learning

Molecular representation learning is crucial for the problem of molecula...

0 Cameron Diao, et al. ∙

research

∙ 12/09/2022

RCDT: Relational Remote Sensing Change Detection with Transformer

Deep learning based change detection methods have received wide attentoi...

0 Kaixuan Lu, et al. ∙

research

∙ 11/18/2022

Contrastive Knowledge Graph Error Detection

Knowledge Graph (KG) errors introduce non-negligible noise, severely aff...

0 Qinggang Zhang, et al. ∙

research

∙ 10/19/2022

RSC: Accelerating Graph Neural Networks Training via Randomized Sparse Computations

The training of graph neural networks (GNNs) is extremely time consuming...

0 Zirui Liu, et al. ∙

research

∙ 09/25/2022

GPatch: Patching Graph Neural Networks for Cold-Start Recommendations

Cold start is an essential and persistent problem in recommender systems...

0 Hao Chen, et al. ∙

research

∙ 09/21/2022

Improving Generalizability of Graph Anomaly Detection Models via Data Augmentation

Graph anomaly detection (GAD) is a vital task since even a few anomalies...

0 Shuang Zhou, et al. ∙

research

∙ 09/14/2022

Graph Contrastive Learning with Personalized Augmentation

Graph contrastive learning (GCL) has emerged as an effective tool for le...

0 Xin Zhang, et al. ∙

research

∙ 08/02/2022

Improvements to enhance robustness of third-order scale-independent WENO-Z schemes

Although there are many improvements to WENO3-Z that target the achievem...

0 Qin Li, et al. ∙

research

∙ 01/07/2022

MGAE: Masked Autoencoders for Self-Supervised Learning on Graphs

We introduce a novel masked graph autoencoder (MGAE) framework to perfor...

0 Qiaoyu Tan, et al. ∙

research

∙ 07/28/2021

Evaluating the weight sensitivity in AHP-based flood risk estimation models

In the analytic hierarchy process (AHP) based flood risk estimation mode...

0 Hongping Zhang, et al. ∙

research

∙ 07/28/2021

Third-order scale-independent WENO-Z scheme achieving optimal order at critical points

As we found previously, when critical points occur within grid intervals...

0 Qin Li, et al. ∙

research

∙ 07/06/2021

Dirichlet Energy Constrained Learning for Deep Graph Neural Networks

Graph neural networks (GNNs) integrate deep architectures and topologica...

0 Kaixiong Zhou, et al. ∙

research

∙ 07/05/2021

An extended watershed-based zonal statistical AHP model for flood risk estimation: Constraining runoff converging related indicators by sub-watersheds

Floods are highly uncertain events, occurring in different regions, with...

0 Hongping Zhang, et al. ∙

research

∙ 06/05/2021

GLSD: The Global Large-Scale Ship Database and Baseline Evaluations

In this paper, we introduce a challenging global large-scale ship databa...

0 Zhenfeng Shao, et al. ∙

research

∙ 05/24/2021

Pan-sharpening via High-pass Modification Convolutional Neural Network

Most existing deep learning-based pan-sharpening methods have several wi...

0 Jiaming Wang, et al. ∙

research

∙ 05/23/2021

SSCAN: A Spatial-spectral Cross Attention Network for Hyperspectral Image Denoising

Hyperspectral images (HSIs) have been widely used in a variety of applic...

0 Zhiqiang Wang, et al. ∙

research

∙ 05/08/2021

Unsupervised Remote Sensing Super-Resolution via Migration Image Prior

Recently, satellites with high temporal resolution have fostered wide at...

56 Jiaming Wang, et al. ∙

research

∙ 04/11/2021

ODT FLOW: A Scalable Platform for Extracting, Analyzing, and Sharing Multi-source Multi-scale Human Mobility

In response to the soaring needs of human mobility data, especially duri...

0 Zhenlong Li, et al. ∙

research

∙ 03/03/2021

Sensing population distribution from satellite imagery via deep learning: model selection, neighboring effect, and systematic biases

The rapid development of remote sensing techniques provides rich, large-...

20 Xiao Huang, et al. ∙

research

∙ 03/01/2021

A Bioinspired Approach-Sensitive Neural Network for Collision Detection in Cluttered and Dynamic Backgrounds

Rapid, accurate and robust detection of looming objects in cluttered mov...

0 Xiao Huang, et al. ∙

research

∙ 03/01/2021

A Bioinspired Retinal Neural Network for Accurately Extracting Small-Target Motion Information in Cluttered Backgrounds

Robust and accurate detection of small moving targets in cluttered movin...

0 Xiao Huang, et al. ∙

research

∙ 02/18/2021

Dynamic Memory based Attention Network for Sequential Recommendation

Sequential recommendation has become increasingly essential in various o...

0 Qiaoyu Tan, et al. ∙

research

∙ 01/27/2021

On developing piecewise rational mapping with fine regulation capability for WENO schemes

On the idea of mapped WENO-JS scheme, properties of mapping methods are ...

0 Qin Li, et al. ∙

research

∙ 11/26/2020

ODT Flow Explorer: Extract, Query, and Visualize Human Mobility

Understanding human mobility dynamics among places provides fundamental ...

0 Zhenlong Li, et al. ∙

research

∙ 08/12/2020

Covariate Balancing Based on Kernel Density Estimates for Controlled Experiments

Controlled experiments are widely used in many applications to investiga...

0 Yiou Li, et al. ∙

research

∙ 06/26/2020

A GRU-based Mixture Density Network for Data-Driven Dynamic Stochastic Programming

The conventional deep learning approaches for solving time-series proble...

0 Xiaoming Li, et al. ∙

research

∙ 06/24/2020

Twitter, human mobility, and COVID-19

The outbreak of COVID-19 highlights the need for a more harmonized, less...

0 Xiao Huang, et al. ∙

research

∙ 06/12/2020

Towards Deeper Graph Neural Networks with Differentiable Group Normalization

Graph neural networks (GNNs), which learn the representation of a node b...

0 Kaixiong Zhou, et al. ∙

research

∙ 05/02/2020

Teaching Machine Comprehension with Compositional Explanations

Advances in extractive machine reading comprehension (MRC) rely heavily ...

0 Qinyuan Ye, et al. ∙

research

∙ 01/20/2020

DDKSP: A Data-Driven Stochastic Programming Framework for Car-Sharing Relocation Problem

Car-sharing issue is a popular research field in sharing economy. In thi...

0 Xiaoming Li, et al. ∙

research

∙ 12/17/2019

Multi-Channel Graph Convolutional Networks

Graph neural networks (GNN) has been demonstrated to be effective in cla...

0 Kaixiong Zhou, et al. ∙

research

∙ 10/09/2019

Learning to Contextually Aggregate Multi-Source Supervision for Sequence Labeling

Sequence labeling is a fundamental framework for various natural languag...

0 Ouyu Lan, et al. ∙

research

∙ 09/25/2019

Learning A Unified Named Entity Tagger From Multiple Partially Annotated Corpora For Efficient Adaptation

Named entity recognition (NER) identifies typed entity mentions in raw t...

0 Xiao Huang, et al. ∙

research

∙ 09/20/2019

A Two-Stage Stochastic Programming Model for Car-Sharing Problem using Kernel Density Estimation

Car-sharing problem is a popular research field in sharing economy. In t...

0 Xiaoming Li, et al. ∙

research

∙ 09/07/2019

Auto-GNN: Neural Architecture Search of Graph Neural Networks

Graph neural networks (GNN) has been successfully applied to operate on ...

0 Kaixiong Zhou, et al. ∙

research

∙ 08/15/2019

A Multimodal Vision Sensor for Autonomous Driving

This paper describes a multimodal vision sensor that integrates three ty...

8 Dongming Sun, et al. ∙

research

∙ 08/11/2019

SpecAE: Spectral AutoEncoder for Anomaly Detection in Attributed Networks

Anomaly detection aims to distinguish observations that are rare and dif...

0 Yuening Li, et al. ∙

research

∙ 05/14/2019

Panoramic Annular Localizer: Tackling the Variation Challenges of Outdoor Localization Using Panoramic Annular Images and Active Deep Descriptors

Visual localization is an attractive problem that estimates the camera l...

1 Ruiqi Cheng, et al. ∙

research

∙ 01/25/2019

A Discrepancy-Based Design for A/B Testing Experiments

The aim of this paper is to introduce a new design of experiment method ...

0 Yiou Li, et al. ∙

research

∙ 01/02/2019

Multi-Label Adversarial Perturbations

Adversarial examples are delicately perturbed inputs, which aim to misle...

0 Qingquan Song, et al. ∙

research

∙ 06/29/2018

A General Multi-agent Epistemic Planner Based on Higher-order Belief Change

In recent years, multi-agent epistemic planning has received attention f...

0 Xiao Huang, et al. ∙

Xiao Huang

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