An empirical study of a test for polynomial relationships in randomly right censored regression models. - Chun-Xia Zhang 002; Chang-Lin Mei; Jiang-She Zhang 001 (Comput. Stat. Data Anal., 2007)

An empirical study of using Rotation Forest to improve regressors. - Chun-Xia Zhang 002; Jiang-She Zhang 001; Guan-Wei Wang (Appl. Math. Comput., 2008)

A local boosting algorithm for solving classification problems. - Chun-Xia Zhang 002; Jiang-She Zhang 001 (Comput. Stat. Data Anal., 2008)

RotBoost: A technique for combining Rotation Forest and AdaBoost. - Chun-Xia Zhang 002; Jiang-She Zhang 001 (Pattern Recognit. Lett., 2008)

An Empirical Study of a Linear Regression Combiner on Multi-class Data Sets. - Chunxia Zhang 002; Robert P. W. Duin (MCS, 2009)

Using Boosting to prune Double-Bagging ensembles. - Chun-Xia Zhang 002; Jiang-She Zhang 001; Gai-Ying Zhang (Comput. Stat. Data Anal., 2009)

A novel method for constructing ensemble classifiers. - Chun-Xia Zhang 002; Jiang-She Zhang 001 (Stat. Comput., 2009)

Out-of-Bag Estimation of the Optimal Hyperparameter in SubBag Ensemble Method. - Gai-Ying Zhang; Chun-Xia Zhang 002; Jiang-She Zhang 001 (Commun. Stat. Simul. Comput., 2010)

A variant of Rotation Forest for constructing ensemble classifiers. - Chun-Xia Zhang 002; Jiang-She Zhang 001 (Pattern Anal. Appl., 2010)

An experimental study of one- and two-level classifier fusion for different sample sizes. - Chunxia Zhang 002; Robert P. W. Duin (Pattern Recognit. Lett., 2011)

Enhancing Spectral Unmixing by Local Neighborhood Weights. - Junmin Liu; Jiangshe Zhang 001; Yuelin Gao; Chunxia Zhang 002; Zhihua Li (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2012)

Boosting variable selection algorithm for linear regression models. - Chun-Xia Zhang 002; Guan-Wei Wang (ICNC, 2014)

Clustering with Prim's sequential representation of minimum spanning tree. - Guan-Wei Wang; Chun-Xia Zhang 002; Jian Zhuang (Appl. Math. Comput., 2014)

IRUSRT: A Novel Imbalanced Learning Technique by Combining Inverse Random Under Sampling and Random Tree. - Chun-Xia Zhang 002; Guan-Wei Wang; Jiang-She Zhang 001; Gao Guo; Qing-Yan Ying (Commun. Stat. Simul. Comput., 2014)

Enhancing performance of restricted Boltzmann machines via log-sum regularization. - Nannan Ji; Jiang-She Zhang 001; Chun-Xia Zhang 002; Qingyan Yin (Knowl. Based Syst., 2014)

A sparse-response deep belief network based on rate distortion theory. - Nan-Nan Ji; Jiang-She Zhang 001; Chun-Xia Zhang 002 (Pattern Recognit., 2014)

Discriminative restricted Boltzmann machine for invariant pattern recognition with linear transformations. - Nannan Ji; Jiang-She Zhang 001; Chun-Xia Zhang 002; Lei Wang (Pattern Recognit. Lett., 2014)

Learning ensemble classifiers via restricted Boltzmann machines. - Chun-Xia Zhang 002; Jiang-She Zhang 001; Nan-Nan Ji; Gao Guo (Pattern Recognit. Lett., 2014)

Building variable selection ensembles for linear regression models by adding noise. - Guan-Wei Wang; Chun-Xia Zhang 002 (ICMLC, 2015)

A Novel Bagging Ensemble Approach for Variable Ranking and Selection for Linear Regression Models. - Chun-Xia Zhang 002; Jiang-She Zhang 001; Guan-Wei Wang (MCS, 2015)

Investigating the Effect of Randomly Selected Feature Subsets on Bagging and Boosting. - Guan-Wei Wang; Chun-Xia Zhang 002; Gao Guo (Commun. Stat. Simul. Comput., 2015)

PBoostGA: pseudo-boosting genetic algorithm for variable ranking and selection. - Chun-Xia Zhang 002; Jiang-She Zhang 001; Sang-Woon Kim (Comput. Stat., 2016)

A new deep neural network based on a stack of single-hidden-layer feedforward neural networks with randomly fixed hidden neurons. - Junying Hu; Jiang-She Zhang 001; Chunxia Zhang 002; Juan Wang (Neurocomputing, 2016)

Randomizing outputs to increase variable selection accuracy. - Chun-Xia Zhang 002; Nan-Nan Ji; Guan-Wei Wang (Neurocomputing, 2016)

Ensembling Variable Selectors by Stability Selection for the Cox Model. - Qing-Yan Yin; Jun-Li Li; Chun-Xia Zhang 002 (Comput. Intell. Neurosci., 2017)

A modified version of Helmholtz machine by using a Restricted Boltzmann Machine to model the generative probability of the top layer. - Junying Hu; Jiang-She Zhang 001; Nannan Ji; Chunxia Zhang 002 (Neurocomputing, 2017)

Generalized extreme learning machine autoencoder and a new deep neural network. - Kai Sun 007; Jiang-She Zhang 001; Chunxia Zhang 002; Junying Hu (Neurocomputing, 2017)

A new regularized restricted Boltzmann machine based on class preserving. - Junying Hu; Jiang-She Zhang 001; Nannan Ji; Chunxia Zhang 002 (Knowl. Based Syst., 2017)

Graph-based discriminative concept factorization for data representation. - Huirong Li; Jiang-She Zhang 001; Junying Hu; Chunxia Zhang 002; Junmin Liu (Knowl. Based Syst., 2017)

A ranking-based strategy to prune variable selection ensembles. - Chun-Xia Zhang 002; Jiang-She Zhang 001; Qingyan Yin (Knowl. Based Syst., 2017)

Variational Bayesian Complex Network Reconstruction. - Shuang Xu; Chun-Xia Zhang 002; Pei Wang 004; Jiang-She Zhang 001 (CoRR, 2018)

An effective hierarchical extreme learning machine based multimodal fusion framework. - Fang Du; Jiangshe Zhang 001; Nannan Ji; Guang Shi; Chunxia Zhang 002 (Neurocomputing, 2018)

Early stopping aggregation in selective variable selection ensembles for high-dimensional linear regression models. - Chun-Xia Zhang 002; Jiang-She Zhang 001; Qing-Yan Yin (Knowl. Based Syst., 2018)

A novel variational Bayesian method for variable selection in logistic regression models. - Chun-Xia Zhang 002; Shuang Xu; Jiang-She Zhang 001 (Comput. Stat. Data Anal., 2019)

Improving text classification with weighted word embeddings via a multi-channel TextCNN model. - Bao Guo; Chunxia Zhang 002; Junmin Liu; Xiaoyi Ma (Neurocomputing, 2019)

Discriminative Representation Learning with Supervised Auto-encoder. - Fang Du; Jiangshe Zhang 001; Nannan Ji; Junying Hu; Chunxia Zhang 002 (Neural Process. Lett., 2019)

Pruning variable selection ensembles. - Chunxia Zhang 002; Yilei Wu; Mu Zhu (Stat. Anal. Data Min., 2019)

Spectral Learning Algorithm Reveals Propagation Capability of Complex Networks. - Shuang Xu; Pei Wang 004; Chun-Xia Zhang 002; Jinhu Lü (IEEE Trans. Cybern., 2019)

DIDFuse: Deep Image Decomposition for Infrared and Visible Image Fusion. - Zixiang Zhao; Shuang Xu; Chunxia Zhang 002; Junmin Liu; Jiangshe Zhang 001; Pengfei Li (IJCAI, 2020)

MFFW: A new dataset for multi-focus image fusion. - Shuang Xu; Xiaoli Wei; Chunxia Zhang 002; Junmin Liu; Jiangshe Zhang 001 (CoRR, 2020)

Efficient and Interpretable Infrared and Visible Image Fusion Via Algorithm Unrolling. - Zixiang Zhao; Shuang Xu; Chunxia Zhang 002; Junmin Liu; Jiangshe Zhang 001 (CoRR, 2020)

Deep Convolutional Sparse Coding Networks for Image Fusion. - Shuang Xu; Zixiang Zhao; Yicheng Wang; Chunxia Zhang 002; Junmin Liu; Jiangshe Zhang 001 (CoRR, 2020)

When Image Decomposition Meets Deep Learning: A Novel Infrared and Visible Image Fusion Method. - Zixiang Zhao; Shuang Xu; Rui Feng; Chunxia Zhang 002; Junmin Liu; Jiangshe Zhang 001 (CoRR, 2020)

Variational Bayesian weighted complex network reconstruction. - Shuang Xu; Chunxia Zhang 002; Pei Wang 004; Jiangshe Zhang 001 (Inf. Sci., 2020)

On selective learning in stochastic stepwise ensembles. - Chun-Xia Zhang 002; Sang-Woon Kim; Jiang-She Zhang 001 (Int. J. Mach. Learn. Cybern., 2020)

Bayesian deep matrix factorization network for multiple images denoising. - Shuang Xu; Chunxia Zhang 002; Jiangshe Zhang 001 (Neural Networks, 2020)

Adaptive quantile low-rank matrix factorization. - Shuang Xu; Chunxia Zhang 002; Jiangshe Zhang 001 (Pattern Recognit., 2020)

Weighted-capsule routing via a fuzzy gaussian model. - Ouafa Amira; Shuang Xu; Fang Du; Jiangshe Zhang 001; Chunxia Zhang 002; Rafik Hamza (Pattern Recognit. Lett., 2020)

PWNet: An Adaptive Weight Network for the Fusion of Panchromatic and Multispectral Images. - Junmin Liu; Yunqiao Feng; Changsheng Zhou; Chunxia Zhang 002 (Remote. Sens., 2020)

PercepPan: Towards Unsupervised Pan-Sharpening Based on Perceptual Loss. - Changsheng Zhou; Jiangshe Zhang 001; Junmin Liu; Chunxia Zhang 002; Rongrong Fei; Shuang Xu (Remote. Sens., 2020)

Bayesian fusion for infrared and visible images. - Zixiang Zhao; Shuang Xu; Chunxia Zhang 002; Junmin Liu; Jiangshe Zhang 001 (Signal Process., 2020)

A distributed parallel training method of deep belief networks. - Guang Shi; Jiangshe Zhang 001; Chunxia Zhang 002; Junying Hu (Soft Comput., 2020)

Robust CP Tensor Factorization With Skew Noise. - Xingfang Huang; Shuang Xu; Chunxia Zhang 002; Jiangshe Zhang 001 (IEEE Signal Process. Lett., 2020)

Towards Reducing Severe Defocus Spread Effects for Multi-Focus Image Fusion via an Optimization Based Strategy. - Shuang Xu; Lizhen Ji; Zhe Wang 025; Pengfei Li; Kai Sun 007; Chunxia Zhang 002; Jiangshe Zhang 001 (IEEE Trans. Computational Imaging, 2020)

HAM-MFN: Hyperspectral and Multispectral Image Multiscale Fusion Network With RAP Loss. - Shuang Xu; Ouafa Amira; Junmin Liu; Chun-Xia Zhang 002; Jiangshe Zhang 001; Guanghai Li (IEEE Trans. Geosci. Remote. Sens., 2020)

Bayesian Transfer Learning for Object Detection in Optical Remote Sensing Images. - Changsheng Zhou; Jiangshe Zhang 001; Junmin Liu; Chunxia Zhang 002; Guang Shi; Junying Hu (IEEE Trans. Geosci. Remote. Sens., 2020)

Deep Gradient Projection Networks for Pan-sharpening. - Shuang Xu; Jiangshe Zhang 001; Zixiang Zhao; Kai Sun 007; Junmin Liu; Chunxia Zhang 002 (CVPR, 2021)

FGF-GAN: A Lightweight Generative Adversarial Network for Pansharpening via Fast Guided Filter. - Zixiang Zhao; Jiangshe Zhang 001; Shuang Xu; Kai Sun 007; Lu Huang; Junmin Liu; Chunxia Zhang 002 (ICME, 2021)

Deep Convolutional Sparse Coding Network For Pansharpening With Guidance Of Side Information. - Shuang Xu; Jiangshe Zhang 001; Kai Sun 007; Zixiang Zhao; Lu Huang; Junmin Liu; Chunxia Zhang 002 (ICME, 2021)

Empirical Evaluation on Utilizing CNN-features for Seismic Patch Classification. - Chun-Xia Zhang 002; Xiaoli Wei; Sang-Woon Kim (ICPRAM, 2021)

Discrete Cosine Transform Network for Guided Depth Map Super-Resolution. - Zixiang Zhao; Jiangshe Zhang 001; Shuang Xu; Chun-Xia Zhang 002; Junmin Liu (CoRR, 2021)

DPP-VSE: Constructing a variable selection ensemble by determinantal point processes. - Chunxia Zhang 002; Junmin Liu; Guanwei Wang; Guanghai Li (Expert Syst. Appl., 2021)

A novel method for Mandarin speech synthesis by inserting prosodic structure prediction into Tacotron2. - Junmin Liu; Zhuangzhuang Xie; Chunxia Zhang 002; Guang Shi (Int. J. Mach. Learn. Cybern., 2021)

CondenseNet with exclusive lasso regularization. - Lizhen Ji; Jiangshe Zhang 001; Chunxia Zhang 002; Cong Ma 005; Shuang Xu; Kai Sun 007 (Neural Comput. Appl., 2021)

MFIF-GAN: A new generative adversarial network for multi-focus image fusion. - Yicheng Wang; Shuang Xu; Junmin Liu; Zixiang Zhao; Chunxia Zhang 002; Jiangshe Zhang 001 (Signal Process. Image Commun., 2021)

Pansharpening Via Neighbor Embedding of Spatial Details. - Junmin Liu; Changsheng Zhou; Rongrong Fei; Chunxia Zhang 002; Jiangshe Zhang 001 (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021)

Global Context-Augmented Objection Detection in VHR Optical Remote Sensing Images. - Guang Shi; Jiang-She Zhang 001; Junmin Liu; Chunxia Zhang 002; Changsheng Zhou; Shuyun Yang (IEEE Trans. Geosci. Remote. Sens., 2021)

Automatic Velocity Picking Using a Multi-Information Fusion Deep Semantic Segmentation Network. - Hongtao Wang; Jiangshe Zhang 001; Zixiang Zhao; Chunxia Zhang 002; Long Li; Zhiyu Yang; Weifeng Geng (CoRR, 2022)

Automatic Velocity Picking Using Unsupervised Ensemble Learning. - Hongtao Wang; Jiangshe Zhang 001; Chunxia Zhang 002; Zixiang Zhao; Chengli Tan; Zhiyu Yang; Weifeng Geng (CoRR, 2022)

MSSPN: Automatic First Arrival Picking using Multi-Stage Segmentation Picking Network. - Hongtao Wang; Jiangshe Zhang 001; Xiaoli Wei; Chunxia Zhang 002; Zhenbo Guo; Li Long; Yicheng Wang (CoRR, 2022)

Forecasting stock volatility and value-at-risk based on temporal convolutional networks. - Chun-Xia Zhang 002; Jun Li; Xing-Fang Huang; Jiang-She Zhang 001; Hua-Chuan Huang (Expert Syst. Appl., 2022)

Seismic fault detection using convolutional neural networks with focal loss. - Xiao-Li Wei; Chunxia Zhang 002; Sang-Woon Kim; Kai-Li Jing; Yong-Jun Wang; Shuang Xu; Zhuangzhuang Xie (Comput. Geosci., 2022)

A model-driven network for guided image denoising. - Shuang Xu; Jiangshe Zhang 001; Jialin Wang; Kai Sun 007; Chunxia Zhang 002; Junmin Liu; Junying Hu (Inf. Fusion, 2022)

Seismic Data Reconstruction via Recurrent Residual Multiscale Inference. - Aoqi Song; Changpeng Wang; Chunxia Zhang 002; Jiang-She Zhang 001; Xiong Deng (IEEE Geosci. Remote. Sens. Lett., 2022)

A Novel Data Augmentation Method for Chinese Character Spatial Structure Recognition by Normalized Deformable Convolutional Networks. - Sheng Zhuo; Jiangshe Zhang 001; Chunxia Zhang 002 (Neural Process. Lett., 2022)

Hyperspectral image denoising by low-rank models with hyper-Laplacian total variation prior. - Shuang Xu; Jiangshe Zhang 001; Chunxia Zhang 002 (Signal Process., 2022)

Efficient and Model-Based Infrared and Visible Image Fusion via Algorithm Unrolling. - Zixiang Zhao; Shuang Xu; Jiangshe Zhang 001; Chengyang Liang; Chunxia Zhang 002; Junmin Liu (IEEE Trans. Circuits Syst. Video Technol., 2022)

Automatic Velocity Picking Using a Multi-Information Fusion Deep Semantic Segmentation Network. - Hongtao Wang; Jiangshe Zhang 001; Zixiang Zhao; Chunxia Zhang 002; Li Long; Zhiyu Yang; Weifeng Geng (IEEE Trans. Geosci. Remote. Sens., 2022)

Hybrid Loss-Guided Coarse-to-Fine Model for Seismic Data Consecutively Missing Trace Reconstruction. - Xiao-Li Wei; Chunxia Zhang 002; Hongtao Wang; Zixiang Zhao; Xiong Deng; Shuang Xu; Jiangshe Zhang 001; Sang-Woon Kim (IEEE Trans. Geosci. Remote. Sens., 2022)

Deep Convolutional Sparse Coding Networks for Interpretable Image Fusion. - Zixiang Zhao; Jiang-She Zhang 001; Haowen Bai; Yicheng Wang; Yukun Cui; Lilun Deng; Kai Sun 007; Chunxia Zhang 002; Junmin Liu; Shuang Xu (CVPR Workshops, 2023)

Leveraging Uncertainty Quantification for Picking Robust First Break Times. - Hongtao Wang; Jiangshe Zhang 001; Xiaoli Wei; Li Long; Chunxia Zhang 002 (CoRR, 2023)

Consecutively Missing Seismic Data Reconstruction Via Wavelet-Based Swin Residual Network. - Pei Liu; Anguo Dong; Changpeng Wang; Chunxia Zhang 002; Jiangshe Zhang 001 (IEEE Geosci. Remote. Sens. Lett., 2023)

Hybrid Shot2Shot and Re-De-Noising Regularization for Random Noise Attenuation of Seismic Data. - Aoqi Song; Changpeng Wang; Chunxia Zhang 002; Jiang-She Zhang 001; Xiao-Li Wei; Xiong Deng (IEEE Geosci. Remote. Sens. Lett., 2023)

Long Short-Term Memory Networks with Multiple Variables for Stock Market Prediction. - Fei Gao; Jiangshe Zhang 001; Chunxia Zhang 002; Shuang Xu; Cong Ma 005 (Neural Process. Lett., 2023)

Regeneration-Constrained Self-Supervised Seismic Data Interpolation. - Aoqi Song; Changpeng Wang; Chunxia Zhang 002; Jiangshe Zhang 001; Xiong Deng; Xiao-Li Wei (IEEE Trans. Geosci. Remote. Sens., 2023)

A reliable Bayesian neural network for the prediction of reservoir thickness with quantified uncertainty. - Li-Li Bao; Jiang-She Zhang 001; Chun-Xia Zhang 002; Rui Guo; Xiao-Li Wei; Zi-Lu Jiang (Comput. Geosci., 2023)

MBIAN: Multi-level bilateral interactive attention network for multi-modal image processing. - Kai Sun 007; Jiangshe Zhang 001; Jialin Wang; Shuang Xu; Chunxia Zhang 002; Junying Hu (Expert Syst. Appl., 2023)

Seismic First Break Picking in a Higher Dimension Using Deep Graph Learning. - Hongtao Wang; Li Long; Jiangshe Zhang 001; Xiaoli Wei; Chunxia Zhang 002; Zhenbo Guo (CoRR, 2024)

A two-stage spatial prediction modeling approach based on graph neural networks and neural processes. - Li-Li Bao; Chun-Xia Zhang 002; Jiang-She Zhang 001; Rui Guo (Expert Syst. Appl., 2024)

Automatic Source Point Offset via REINFORCE Based on Transformer. - Li Long; Chunxia Zhang 002; Hongtao Wang; Li-Li Bao; Jiangshe Zhang 001; Yan Wang; Huibing Zhao (IEEE Geosci. Remote. Sens. Lett., 2024)

Spatial multi-attention conditional neural processes. - Li-Li Bao; Jiang-She Zhang 001; Chunxia Zhang 002 (Neural Networks, 2024)

Simultaneous Automatic Picking and Manual Picking Refinement for First-Break. - Haowen Bai; Zixiang Zhao; Jiangshe Zhang 001; Yukun Cui; Chunxia Zhang 002; Zhenbo Guo; Yongjun Wang (IEEE Trans. Geosci. Remote. Sens., 2024)

DSU-Net: Dynamic Snake U-Net for 2-D Seismic First Break Picking. - Hongtao Wang; Rongyu Feng; Liangyi Wu; Mutian Liu; Yinuo Cui; Chunxia Zhang 002; Zhenbo Guo (IEEE Trans. Geosci. Remote. Sens., 2024)

UPNet: Uncertainty-Based Picking Deep Learning Network for Robust First Break Picking. - Hongtao Wang; Jiangshe Zhang 001; Xiao-Li Wei; Li Long; Chunxia Zhang 002; Zhenbo Guo (IEEE Trans. Geosci. Remote. Sens., 2024)

Seismic Data Interpolation via Denoising Diffusion Implicit Models With Coherence-Corrected Resampling. - Xiao-Li Wei; Chunxia Zhang 002; Hongtao Wang; Chengli Tan; Deng Xiong; Baisong Jiang; Jiangshe Zhang 001; Sang-Woon Kim (IEEE Trans. Geosci. Remote. Sens., 2024)

Self-similar spectral reasoning network for efficient anti-aliasing seismic data reconstruction. - Xin Geng; Changpeng Wang; Aoqi Song; Chunxia Zhang 002; Jiangshe Zhang 001; Zhiliang Zhou (Eng. Appl. Artif. Intell., 2025)

Seismic data reconstruction via an adaptive feature fusion network. - Yuting Mu; Changpeng Wang; Xin Geng; Chunxia Zhang 002; Jiangshe Zhang 001; Junxiong Jia (Eng. Appl. Artif. Intell., 2025)

Automatic fault interpretation method embedded with clustering task in 3D-UNet3+. - Chunxia Zhang 002; Qing Zou; Jiang-She Zhang 001; Yongjun Wang; Lu Huang; Chunfeng Tao (Expert Syst. Appl., 2025)

CoFM: Alternating convolution and frequency module is also strong for visual recognition. - Jiayong Bao; Jiangshe Zhang 001; Chunxia Zhang 002 (Neurocomputing, 2025)

FDSANet: Seismic Data Reconstruction Based on a Frequency-Domain Self-Attention Network. - Yuting Mu; Changpeng Wang; Xin Geng; Chunxia Zhang 002; Jiangshe Zhang 001 (IEEE Geosci. Remote. Sens. Lett., 2025)

DCTCNet: Sequency discrete cosine transform convolution network for visual recognition. - Jiayong Bao; Jiangshe Zhang 001; Chunxia Zhang 002; Li-Li Bao (Neural Networks, 2025)

An information-theoretic learning model based on importance sampling with application in face verification. - Jiang-She Zhang 001; Lizhen Ji; Fei Gao; Mengyao Li; Chunxia Zhang 002; Yukun Cui (Pattern Recognit. Lett., 2025)

A Label-Free High-Precision Residual Moveout Picking Method for Travel Time Tomography based on Deep Learning. - Hongtao Wang; Jiandong Liang; Lei Wang; Shuaizhe Liang; Jinping Zhu; Chunxia Zhang 002; Jiangshe Zhang 001 (CoRR, 2025)

CACNN: Capsule Attention Convolutional Neural Networks for 3D Object Recognition. - Kai Sun 007; Jiangshe Zhang 001; Shuang Xu; Zixiang Zhao; Chunxia Zhang 002; Junmin Liu; Junying Hu (IEEE Trans. Neural Networks Learn. Syst., 2025)

Deep Unfolding Multi-Modal Image Fusion Network via Attribution Analysis. - Haowen Bai; Zixiang Zhao; Jiangshe Zhang 001; Baisong Jiang; Lilun Deng; Yukun Cui; Shuang Xu; Chunxia Zhang 002 (IEEE Trans. Circuits Syst. Video Technol., 2025)