661 citations · 1.4k across the 47 of their papers we have counts for
49 papers
Graph Neural Networks with Diverse Spectral Filtering
Jingwei Guo, Kaizhu Huang, Xinping Yi +1
Spectral Graph Neural Networks (GNNs) have achieved tremendous success in graph machine learning, with polynomial filters applied for graph convolutions, where all nodes share the…
Learning by Analogy: Diverse Questions Generation in Math Word Problem
Zihao Zhou, Maizhen Ning, Qiufeng Wang +4
Solving math word problem (MWP) with AI techniques has recently made great progress with the success of deep neural networks (DNN), but it is far from being solved. We argue that t…
Can Perturbations Help Reduce Investment Risks? Risk-Aware Stock Recommendation via Split Variational Adversarial Training
Jiezhu Cheng, Kaizhu Huang, Zibin Zheng
In the stock market, a successful investment requires a good balance between profits and risks. Based on the learning to rank paradigm, stock recommendation has been widely studied…
A generalizable framework for low-rank tensor completion with numerical priors
Shiran Yuan, Kaizhu Huang
Low-Rank Tensor Completion, a method which exploits the inherent structure of tensors, has been studied extensively as an effective approach to tensor completion. Whilst such metho…
Towards Deeper and Better Multi-view Feature Fusion for 3D Semantic Segmentation
Chaolong Yang, Yuyao Yan, Weiguang Zhao +4
3D point clouds are rich in geometric structure information, while 2D images contain important and continuous texture information. Combining 2D information to achieve better 3D sem…
Deep Learning for Brain Age Estimation: A Systematic Review
M. Tanveer, M. A. Ganaie, Iman Beheshti +7
Over the years, Machine Learning models have been successfully employed on neuroimaging data for accurately predicting brain age. Deviations from the healthy brain aging pattern ar…
Rethinking Data Augmentation for Single-source Domain Generalization in Medical Image Segmentation
Zixian Su, Kai Yao, Xi Yang +3
Single-source domain generalization (SDG) in medical image segmentation is a challenging yet essential task as domain shifts are quite common among clinical image datasets. Previou…
SSD: Towards Better Text-Image Consistency Metric in Text-to-Image Generation
Zhaorui Tan, Xi Yang, Zihan Ye +4
Generating consistent and high-quality images from given texts is essential for visual-language understanding. Although impressive results have been achieved in generating high-qua…
Rebalanced Zero-shot Learning
Zihan Ye, Guanyu Yang, Xiaobo Jin +2
Zero-shot learning (ZSL) aims to identify unseen classes with zero samples during training. Broadly speaking, present ZSL methods usually adopt class-level semantic labels and comp…
EgPDE-Net: Building Continuous Neural Networks for Time Series Prediction with Exogenous Variables
Penglei Gao, Xi Yang, Rui Zhang +3
While exogenous variables have a major impact on performance improvement in time series analysis, inter-series correlation and time dependence among them are rarely considered in t…
Outpainting by Queries
Kai Yao, Penglei Gao, Xi Yang +3
Image outpainting, which is well studied with Convolution Neural Network (CNN) based framework, has recently drawn more attention in computer vision. However, CNNs rely on inherent…
Divide and Conquer: 3D Point Cloud Instance Segmentation With Point-Wise Binarization
Weiguang Zhao, Yuyao Yan, Chaolong Yang +3
Instance segmentation on point clouds is crucially important for 3D scene understanding. Most SOTAs adopt distance clustering, which is typically effective but does not perform wel…
ES-GNN: Generalizing Graph Neural Networks Beyond Homophily with Edge Splitting
Jingwei Guo, Kaizhu Huang, Rui Zhang +1
While Graph Neural Networks (GNNs) have achieved enormous success in multiple graph analytical tasks, modern variants mostly rely on the strong inductive bias of homophily. However…
Mind The Gap: Alleviating Local Imbalance for Unsupervised Cross-Modality Medical Image Segmentation
Zixian Su, Kai Yao, Xi Yang +4
Unsupervised cross-modality medical image adaptation aims to alleviate the severe domain gap between different imaging modalities without using the target domain label. A key in th…
From 2D Images to 3D Model:Weakly Supervised Multi-View Face Reconstruction with Deep Fusion
Weiguang Zhao, Chaolong Yang, Jianan Ye +6
While weakly supervised multi-view face reconstruction (MVR) is garnering increased attention, one critical issue still remains open: how to effectively interact and fuse multiple…
A Survey of Robust Adversarial Training in Pattern Recognition: Fundamental, Theory, and Methodologies
Zhuang Qian, Kaizhu Huang, Qiu-Feng Wang +1
In the last a few decades, deep neural networks have achieved remarkable success in machine learning, computer vision, and pattern recognition. Recent studies however show that neu…
Towards Simple and Accurate Human Pose Estimation with Stair Network
Chenru Jiang, Kaizhu Huang, Shufei Zhang +3
In this paper, we focus on tackling the precise keypoint coordinates regression task. Most existing approaches adopt complicated networks with a large number of parameters, leading…
Generalised Image Outpainting with U-Transformer
Penglei Gao, Xi Yang, Rui Zhang +4
In this paper, we develop a novel transformer-based generative adversarial neural network called U-Transformer for generalised image outpainting problem. Different from most presen…
PointNu-Net: Keypoint-assisted Convolutional Neural Network for Simultaneous Multi-tissue Histology Nuclei Segmentation and Classification
Kai Yao, Kaizhu Huang, Jie Sun +1
Automatic nuclei segmentation and classification play a vital role in digital pathology. However, previous works are mostly built on data with limited diversity and small sizes, ma…
Each Attribute Matters: Contrastive Attention for Sentence-based Image Editing
Liuqing Zhao, Fan Lyu, Fuyuan Hu +3
Sentence-based Image Editing (SIE) aims to deploy natural language to edit an image. Offering potentials to reduce expensive manual editing, SIE has attracted much interest recentl…
Reborn Mechanism: Rethinking the Negative Phase Information Flow in Convolutional Neural Network
Zhicheng Cai, Kaizhu Huang, Chenglei Peng
This paper proposes a novel nonlinear activation mechanism typically for convolutional neural network (CNN), named as reborn mechanism. In sharp contrast to ReLU which cuts off the…
AD-GAN: End-to-end Unsupervised Nuclei Segmentation with Aligned Disentangling Training
Kai Yao, Kaizhu Huang, Jie Sun +1
We consider unsupervised cell nuclei segmentation in this paper. Exploiting the recently-proposed unpaired image-to-image translation between cell nuclei images and randomly synthe…
Improving Model Robustness with Latent Distribution Locally and Globally
Zhuang Qian, Shufei Zhang, Kaizhu Huang +3
In this work, we consider model robustness of deep neural networks against adversarial attacks from a global manifold perspective. Leveraging both the local and global latent infor…
Disentangling Semantic-to-visual Confusion for Zero-shot Learning
Zihan Ye, Fuyuan Hu, Fan Lyu +2
Using generative models to synthesize visual features from semantic distribution is one of the most popular solutions to ZSL image classification in recent years. The triplet loss…