b'Lifang He'

research

∙ 09/05/2023

Unsupervised Skin Lesion Segmentation via Structural Entropy Minimization on Multi-Scale Superpixel Graphs

Skin lesion segmentation is a fundamental task in dermoscopic image anal...

0 Guangjie Zeng, et al. ∙

research

∙ 07/27/2023

One-shot Joint Extraction, Registration and Segmentation of Neuroimaging Data

Brain extraction, registration and segmentation are indispensable prepro...

0 Yao Su, et al. ∙

research

∙ 05/11/2023

Deep Multi-View Subspace Clustering with Anchor Graph

Deep multi-view subspace clustering (DMVSC) has recently attracted incre...

0 Chenhang Cui, et al. ∙

research

∙ 04/24/2023

Hierarchical State Abstraction Based on Structural Information Principles

State abstraction optimizes decision-making by ignoring irrelevant envir...

0 Xianghua Zeng, et al. ∙

research

∙ 04/18/2023

A Comparison of Image Denoising Methods

The advancement of imaging devices and countless images generated everyd...

0 Zhaoming Kong, et al. ∙

research

∙ 03/21/2023

Self-Paced Neutral Expression-Disentangled Learning for Facial Expression Recognition

The accuracy of facial expression recognition is typically affected by t...

0 Zhenqian Wu, et al. ∙

research

∙ 02/18/2023

A Comprehensive Survey on Pretrained Foundation Models: A History from BERT to ChatGPT

The Pretrained Foundation Models (PFMs) are regarded as the foundation f...

0 Ce Zhou, et al. ∙

research

∙ 12/06/2022

ERNet: Unsupervised Collective Extraction and Registration in Neuroimaging Data

Brain extraction and registration are important preprocessing steps in n...

0 Yao Su, et al. ∙

research

∙ 12/06/2022

ABN: Anti-Blur Neural Networks for Multi-Stage Deformable Image Registration

Deformable image registration, i.e., the task of aligning multiple image...

0 Yao Su, et al. ∙

research

∙ 11/13/2022

Normative Modeling via Conditional Variational Autoencoder and Adversarial Learning to Identify Brain Dysfunction in Alzheimer's Disease

Normative modeling is an emerging and promising approach to effectively ...

0 Xuetong Wang, et al. ∙

research

∙ 10/13/2022

Variational Graph Generator for Multi-View Graph Clustering

Multi-view graph clustering (MGC) methods are increasingly being studied...

0 Jianpeng Chen, et al. ∙

research

∙ 10/09/2022

Deep Clustering: A Comprehensive Survey

Cluster analysis plays an indispensable role in machine learning and dat...

0 Yazhou Ren, et al. ∙

research

∙ 09/23/2022

Tensor-Based Multi-Modality Feature Selection and Regression for Alzheimer's Disease Diagnosis

The assessment of Alzheimer's Disease (AD) and Mild Cognitive Impairment...

0 Jun Yu, et al. ∙

research

∙ 06/30/2022

Interpretable Graph Neural Networks for Connectome-Based Brain Disorder Analysis

Human brains lie at the core of complex neurobiological systems, where t...

13 Hejie Cui, et al. ∙

research

∙ 06/09/2022

Data-Efficient Brain Connectome Analysis via Multi-Task Meta-Learning

Brain networks characterize complex connectivities among brain regions a...

13 Yi Yang, et al. ∙

research

∙ 05/08/2022

Deep Embedded Multi-View Clustering via Jointly Learning Latent Representations and Graphs

With the representation learning capability of the deep learning models,...

0 Zongmo Huang, et al. ∙

research

∙ 04/27/2022

Interpretable Graph Convolutional Network of Multi-Modality Brain Imaging for Alzheimer's Disease Diagnosis

Identification of brain regions related to the specific neurological dis...

0 Houliang Zhou, et al. ∙

research

∙ 03/18/2022

Deep Reinforcement Learning Guided Graph Neural Networks for Brain Network Analysis

Modern neuroimaging techniques, such as diffusion tensor imaging (DTI) a...

0 Xusheng Zhao, et al. ∙

research

∙ 03/17/2022

BrainGB: A Benchmark for Brain Network Analysis with Graph Neural Networks

Mapping the connectome of the human brain using structural or functional...

0 Hejie Cui, et al. ∙

research

∙ 02/09/2022

Task Modifiers for HTN Planning and Acting

The ability of an agent to change its objectives in response to unexpect...

0 Weihang Yuan, et al. ∙

research

∙ 02/08/2022

Deep learning for drug repurposing: methods, databases, and applications

Drug development is time-consuming and expensive. Repurposing existing d...

15 Xiaoqin Pan, et al. ∙

research

∙ 11/21/2021

Structure-Preserving Graph Kernel for Brain Network Classification

This paper presents a novel graph-based kernel learning approach for con...

0 Zhaomin Kong, et al. ∙

research

∙ 10/12/2021

HETFORMER: Heterogeneous Transformer with Sparse Attention for Long-Text Extractive Summarization

To capture the semantic graph structure from raw text, most existing sum...

0 Ye Liu, et al. ∙

research

∙ 07/31/2021

Multiplex Graph Networks for Multimodal Brain Network Analysis

In this paper, we propose MGNet, a simple and effective multiplex graph ...

0 Zhaoming Kong, et al. ∙

research

∙ 07/11/2021

BrainNNExplainer: An Interpretable Graph Neural Network Framework for Brain Network based Disease Analysis

Interpretable brain network models for disease prediction are of great v...

25 Hejie Cui, et al. ∙

research

∙ 07/07/2021

Joint Embedding of Structural and Functional Brain Networks with Graph Neural Networks for Mental Illness Diagnosis

Multimodal brain networks characterize complex connectivities among diff...

10 Yanqiao Zhu, et al. ∙

research

∙ 06/21/2021

Multi-VAE: Learning Disentangled View-common and View-peculiar Visual Representations for Multi-view Clustering

Multi-view clustering, a long-standing and important research problem, f...

0 Jie Xu, et al. ∙

research

∙ 06/21/2021

Contrastive Multi-Modal Clustering

Multi-modal clustering, which explores complementary information from mu...

0 Jie Xu, et al. ∙

research

∙ 05/22/2021

A Robust and Generalized Framework for Adversarial Graph Embedding

Graph embedding is essential for graph mining tasks. With the prevalence...

5 Jianxin Li, et al. ∙

research

∙ 05/07/2021

Graph Entropy Guided Node Embedding Dimension Selection for Graph Neural Networks

Graph representation learning has achieved great success in many areas, ...

12 Gongxu Luo, et al. ∙

research

∙ 05/07/2021

Error-Robust Multi-View Clustering: Progress, Challenges and Opportunities

With recent advances in data collection from multiple sources, multi-vie...

7 Mehrnaz Najafi, et al. ∙

research

∙ 05/04/2021

Federated Multi-View Learning for Private Medical Data Integration and Analysis

Along with the rapid expansion of information technology and digitalizat...

11 Sicong Che, et al. ∙

research

∙ 04/19/2021

Non-Linear Fusion for Self-Paced Multi-View Clustering

With the advance of the multi-media and multi-modal data, multi-view clu...

0 Zongmo Huang, et al. ∙

research

∙ 04/16/2021

Higher-Order Attribute-Enhancing Heterogeneous Graph Neural Networks

Graph neural networks (GNNs) have been widely used in deep learning on g...

9 Jianxin Li, et al. ∙

research

∙ 04/02/2021

Streaming Social Event Detection and Evolution Discovery in Heterogeneous Information Networks

Events are happening in real-world and real-time, which can be planned a...

9 Hao Peng, et al. ∙

research

∙ 02/06/2021

FedMood:Federated Learning on Mobile Health Data for Mood Detection

Depression is one of the most common mental illness problems, and the sy...

0 Xiaohang Xu, et al. ∙

research

∙ 01/20/2021

SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism

Graph representation learning has attracted increasing research attentio...

0 Qingyun Sun, et al. ∙

research

∙ 01/17/2021

Heterogeneous Similarity Graph Neural Network on Electronic Health Records

Mining Electronic Health Records (EHRs) becomes a promising topic becaus...

13 Zheng Liu, et al. ∙

research

∙ 12/10/2020

CommPOOL: An Interpretable Graph Pooling Framework for Hierarchical Graph Representation Learning

Recent years have witnessed the emergence and flourishing of hierarchica...

0 Haoteng Tang, et al. ∙

research

∙ 11/06/2020

A Comprehensive Comparison of Multi-Dimensional Image Denoising Methods

Filtering multi-dimensional images such as color images, color videos, m...

29 Zhaoming Kong, et al. ∙

research

∙ 11/02/2020

Hierarchical Bi-Directional Self-Attention Networks for Paper Review Rating Recommendation

Review rating prediction of text reviews is a rapidly growing technology...

29 Zhongfen Deng, et al. ∙

research

∙ 10/05/2020

Mixup-Transfomer: Dynamic Data Augmentation for NLP Tasks

Mixup is the latest data augmentation technique that linearly interpolat...

0 Lichao Sun, et al. ∙

research

∙ 09/26/2020

KG-BART: Knowledge Graph-Augmented BART for Generative Commonsense Reasoning

Generative commonsense reasoning which aims to empower machines to gener...

0 Ye Liu, et al. ∙

research

∙ 08/30/2020

Pairwise Learning for Name Disambiguation in Large-Scale Heterogeneous Academic Networks

Name disambiguation aims to identify unique authors with the same name. ...

24 Qingyun Sun, et al. ∙

research

∙ 08/12/2020

Lifelong Property Price Prediction: A Case Study for the Toronto Real Estate Market

We present Luce, the first life-long predictive model for automated prop...

0 Hao Peng, et al. ∙

research

∙ 08/09/2020

Adversarial Directed Graph Embedding

Node representation learning for directed graphs is critically important...

0 Shijie Zhu, et al. ∙

research

∙ 08/02/2020

A Survey on Text Classification: From Shallow to Deep Learning

Text classification is the most fundamental and essential task in natura...

0 Qian Li, et al. ∙

research

∙ 10/17/2019

Not Just Cloud Privacy: Protecting Client Privacy in Teacher-Student Learning

Ensuring the privacy of sensitive data used to train modern machine lear...

0 Lichao Sun, et al. ∙

research

∙ 06/09/2019

Hierarchical Taxonomy-Aware and Attentional Graph Capsule RCNNs for Large-Scale Multi-Label Text Classification

CNNs, RNNs, GCNs, and CapsNets have shown significant insights in repres...

6 Hao Peng, et al. ∙

research

∙ 11/03/2018

Boosted Sparse and Low-Rank Tensor Regression

We propose a sparse and low-rank tensor regression model to relate a uni...

0 Lifang He, et al. ∙

Lifang He

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