b'Ming Zhang'

research

∙ 09/21/2023

Dynamic Hypergraph Structure Learning for Traffic Flow Forecasting

This paper studies the problem of traffic flow forecasting, which aims t...

0 Yusheng Zhao, et al. ∙

research

∙ 08/31/2023

Towards Long-Tailed Recognition for Graph Classification via Collaborative Experts

Graph classification, aiming at learning the graph-level representations...

0 Siyu Yi, et al. ∙

research

∙ 08/04/2023

RAHNet: Retrieval Augmented Hybrid Network for Long-tailed Graph Classification

Graph classification is a crucial task in many real-world multimedia app...

0 Zhengyang Mao, et al. ∙

research

∙ 06/28/2023

Erasing-based lossless compression method for streaming floating-point time series

There are a prohibitively large number of floating-point time series dat...

0 Ruiyuan Li, et al. ∙

research

∙ 06/14/2023

Learning on Graphs under Label Noise

Node classification on graphs is a significant task with a wide range of...

0 Jingyang Yuan, et al. ∙

research

∙ 05/31/2023

Towards Semi-supervised Universal Graph Classification

Graph neural networks have pushed state-of-the-arts in graph classificat...

0 Xiao Luo, et al. ∙

research

∙ 05/18/2023

MolXPT: Wrapping Molecules with Text for Generative Pre-training

Generative pre-trained Transformer (GPT) has demonstrates its great succ...

0 Zequn Liu, et al. ∙

research

∙ 04/14/2023

Learning Graph ODE for Continuous-Time Sequential Recommendation

Sequential recommendation aims at understanding user preference by captu...

0 Yifang Qin, et al. ∙

research

∙ 04/14/2023

A Diffusion model for POI recommendation

Next Point-of-Interest (POI) recommendation is a critical task in locati...

0 Yifang Qin, et al. ∙

research

∙ 04/11/2023

A Comprehensive Survey on Deep Graph Representation Learning

Graph representation learning aims to effectively encode high-dimensiona...

0 Wei Ju, et al. ∙

research

∙ 03/29/2023

Robust Dancer: Long-term 3D Dance Synthesis Using Unpaired Data

How to automatically synthesize natural-looking dance movements based on...

0 Bin Feng, et al. ∙

research

∙ 03/27/2023

Disruption Precursor Onset Time Study Based on Semi-supervised Anomaly Detection

The full understanding of plasma disruption in tokamaks is currently lac...

0 Xinkun Ai, et al. ∙

research

∙ 01/13/2023

Channel Measurement for Holographic MIMO: Benefits and Challenges of Spatial Oversampling

In this paper, the channel of an indoor holographic multiple-input multi...

0 Tengjiao Wang, et al. ∙

research

∙ 12/05/2022

2D Human Pose Estimation with Explicit Anatomical Keypoints Structure Constraints

Recently, human pose estimation mainly focuses on how to design a more e...

0 Zhangjian Ji, et al. ∙

research

∙ 11/13/2022

TIER-A: Denoising Learning Framework for Information Extraction

With the development of deep neural language models, great progress has ...

0 Yongkang Li, et al. ∙

research

∙ 10/21/2022

GLCC: A General Framework for Graph-level Clustering

This paper studies the problem of graph-level clustering, which is a nov...

0 Wei Ju, et al. ∙

research

∙ 10/14/2022

MetaFill: Text Infilling for Meta-Path Generation on Heterogeneous Information Networks

Heterogeneous Information Network (HIN) is essential to study complicate...

0 Zequn Liu, et al. ∙

research

∙ 09/01/2022

Focus-Driven Contrastive Learniang for Medical Question Summarization

Automatic medical question summarization can significantly help the syst...

0 Ming Zhang, et al. ∙

research

∙ 08/20/2022

Transferable Cross-Tokamak Disruption Prediction with Deep Hybrid Neural Network Feature Extractor

Predicting disruptions across different tokamaks is a great obstacle to ...

0 Wei Zheng, et al. ∙

research

∙ 06/28/2022

Taxonomy and evolution predicting using deep learning in images

Molecular and morphological characters, as important parts of biological...

0 Jiewen Xiao, et al. ∙

research

∙ 06/07/2022

Learning to Efficiently Propagate for Reasoning on Knowledge Graphs

Path-based methods are more appealing solutions than embedding methods f...

8 Zhaocheng Zhu, et al. ∙

research

∙ 05/21/2022

KGNN: Harnessing Kernel-based Networks for Semi-supervised Graph Classification

This paper studies semi-supervised graph classification, which is an imp...

5 Wei Ju, et al. ∙

research

∙ 05/08/2022

End-to-End Rubbing Restoration Using Generative Adversarial Networks

Rubbing restorations are significant for preserving world cultural histo...

0 Gongbo Sun, et al. ∙

research

∙ 09/09/2021

Graphine: A Dataset for Graph-aware Terminology Definition Generation

Precisely defining the terminology is the first step in scientific commu...

11 Zequn Liu, et al. ∙

research

∙ 07/27/2021

QoS-aware User Grouping Strategy for Downlink Multi-Cell NOMA Systems

In multi-cell non-orthogonal multiple access (NOMA) systems, designing a...

0 Fengqian Guo, et al. ∙

research

∙ 07/01/2021

Orthonormal Product Quantization Network for Scalable Face Image Retrieval

Recently, deep hashing with Hamming distance metric has drawn increasing...

0 Ming Zhang, et al. ∙

research

∙ 03/26/2021

IMU Data Processing For Inertial Aided Navigation: A Recurrent Neural Network Based Approach

In this work, we propose a novel method for performing inertial aided na...

0 Ming Zhang, et al. ∙

research

∙ 03/17/2021

Improved Deep Classwise Hashing With Centers Similarity Learning for Image Retrieval

Deep supervised hashing for image retrieval has attracted researchers' a...

0 Ming Zhang, et al. ∙

research

∙ 01/21/2021

MoG-QSM: Model-based Generative Adversarial Deep Learning Network for Quantitative Susceptibility Mapping

Quantitative susceptibility mapping (QSM) estimates the underlying tissu...

17 Ruimin Feng, et al. ∙

research

∙ 01/15/2021

QoS-Driven Video Uplinking in NOMA-Based IoT

In recent years, with the explosive growth of visual sensors and a large...

0 Pengfei Ma, et al. ∙

research

∙ 12/14/2020

Learning Hybrid Representations for Automatic 3D Vessel Centerline Extraction

Automatic blood vessel extraction from 3D medical images is crucial for ...

10 Jiafa He, et al. ∙

research

∙ 10/11/2020

Partial FC: Training 10 Million Identities on a Single Machine

Face recognition has been an active and vital topic among computer visio...

16 Xiang An, et al. ∙

research

∙ 10/09/2020

Rethinking the Extraction and Interaction of Multi-Scale Features for Vessel Segmentation

Analyzing the morphological attributes of blood vessels plays a critical...

8 Yicheng Wu, et al. ∙

research

∙ 09/23/2020

MAFF-Net: Filter False Positive for 3D Vehicle Detection with Multi-modal Adaptive Feature Fusion

3D vehicle detection based on multi-modal fusion is an important task of...

2 Zehan Zhang, et al. ∙

research

∙ 09/01/2020

RangeRCNN: Towards Fast and Accurate 3D Object Detection with Range Image Representation

We present RangeRCNN, a novel and effective 3D object detection framewor...

5 Zhidong Liang, et al. ∙

research

∙ 08/16/2020

Association and Caching in Relay-Assisted mmWave Networks: From A Stochastic Geometry Perspective

Limited backhaul bandwidth and blockage effects are two main factors lim...

0 Zhuojia Gu, et al. ∙

research

∙ 07/15/2020

Augmented Bi-path Network for Few-shot Learning

Few-shot Learning (FSL) which aims to learn from few labeled training da...

0 Baoming Yan, et al. ∙

research

∙ 06/30/2020

EasyQuant: Post-training Quantization via Scale Optimization

The 8 bits quantization has been widely applied to accelerate network in...

0 Di Wu, et al. ∙

research

∙ 06/05/2020

Wasserstein Distance guided Adversarial Imitation Learning with Reward Shape Exploration

The generative adversarial imitation learning (GAIL) has provided an adv...

8 Ming Zhang, et al. ∙

research

∙ 05/24/2020

When does MAML Work the Best? An Empirical Study on Model-Agnostic Meta-Learning in NLP Applications

Model-Agnostic Meta-Learning (MAML), a model-agnostic meta-learning meth...

0 Zequn Liu, et al. ∙

research

∙ 04/11/2020

Multi-task Learning via Adaptation to Similar Tasks for Mortality Prediction of Diverse Rare Diseases

Mortality prediction of diverse rare diseases using electronic health re...

0 Luchen Liu, et al. ∙

research

∙ 03/28/2020

A Graph to Graphs Framework for Retrosynthesis Prediction

A fundamental problem in computational chemistry is to find a set of rea...

2 Chence Shi, et al. ∙

research

∙ 01/26/2020

GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation

Molecular graph generation is a fundamental problem for drug discovery a...

20 Chence Shi, et al. ∙

research

∙ 12/25/2019

Learning to Answer Ambiguous Questions with Knowledge Graph

In the task of factoid question answering over knowledge base, many ques...

9 Yikai Zhu, et al. ∙

research

∙ 11/12/2019

Predictive Multi-level Patient Representations from Electronic Health Records

The advent of the Internet era has led to an explosive growth in the Ele...

0 Zichang Wang, et al. ∙

research

∙ 11/09/2019

PoD: Positional Dependency-Based Word Embedding for Aspect Term Extraction

Dependency context-based word embedding jointly learns the representatio...

0 Yichun Yin, et al. ∙

research

∙ 10/31/2019

Learning to Customize Language Model for Generation-based dialog systems

Personalized conversation systems have received increasing attention rec...

0 Yiping Song, et al. ∙

research

∙ 10/14/2019

Early Prediction of Sepsis From Clinical Datavia Heterogeneous Event Aggregation

Sepsis is a life-threatening condition that seriously endangers millions...

0 Luchen Liu, et al. ∙

research

∙ 09/13/2019

Towards Open-Domain Named Entity Recognition via Neural Correction Models

Named Entity Recognition (NER) plays an important role in a wide range o...

0 Mengdi Zhu, et al. ∙

research

∙ 09/11/2019

A Lightweight and Accurate Localization Algorithm Using Multiple Inertial Measurement Units

In this paper, a lightweight and accurate localization algorithm is prop...

0 Ming Zhang, et al. ∙

Ming Zhang

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