Content-Adaptive Rain and Snow Removal Algorithms for Single Image. - Shujian Yu; Yixiao Zhao; Yi Mou; Jinghui Wu; Lu Han; Xiaopeng Yang; Baojun Zhao (ISNN, 2014)

Data-Driven Bridge Detection in Compressed Domain from Panchromatic Satellite Imagery. - Yixiao Zhao; Shujian Yu; Jinghui Wu; Lu Han; Zijing Chen; Xiaopeng Yang; Baojun Zhao (ISNN, 2014)

A general solution for multi-thread based multi-source compressed video surveillance system. - Lu Han; Yixiao Zhao; Shujian Yu; Baojun Zhao; Jiatong Li 004; Jinghui Wu (SPAC, 2014)

Gaussian latent variable models for variable selection. - Xiubao Jiang; Xinge You; Yi Mou; Shujian Yu; Wu Zeng (SPAC, 2014)

Global sparse partial least squares. - Yi Mou; Xinge You; Xiubao Jiang; Duanquan Xu; Shujian Yu (SPAC, 2014)

STFT-like time frequency representations for nonstationary signal - From evenly sampled data to arbitrary nonuniformly sampled data. - Shujian Yu; Xinge You; Kexin Zhao; Xiubao Jiang; Yi Mou; Jie Zhu (SPAC, 2014)

Robust weighted coarse-to-fine sparse tracking. - Boxuan Zhong; Zijing Chen; Xinge You; Luoqing Li; Yunliang Xie; Shujian Yu (SPAC, 2014)

Single image rain streaks removal based on self-learning and structured sparse representation. - Shujian Yu; Weihua Ou; Xinge You; Yi Mou; Xiubao Jiang; Yuanyan Tang (ChinaSIP, 2015)

Robust Discriminative Nonnegative Patch Alignment for Occluded Face Recognition. - Weihua Ou; Gai Li; Shujian Yu; Gang Xie; Fujia Ren; Yuanyan Tang (ICONIP (4), 2015)

Webcam-Based Visual Gaze Estimation Under Desktop Environment. - Shujian Yu; Weihua Ou; Xinge You; Xiubao Jiang; Yun Zhu; Yi Mou; Weigang Guo; Yuanyan Tang; C. L. Philip Chen (ICONIP (2), 2015)

Generalized Kernel Normalized Mixed-Norm Algorithm: Analysis and Simulations. - Shujian Yu; Xinge You; Xiubao Jiang; Weihua Ou; Ziqi Zhu; Yixiao Zhao; C. L. Philip Chen; Yuanyan Tang (ICONIP (2), 2015)

Kernel normalized mixed-norm algorithm for system identification. - Shujian Yu; Xinge You; Kexin Zhao; Weihua Ou; Yuanyan Tang (IJCNN, 2015)

Dynamic Texture Synthesis via Image Reconstruction. - Weigang Guo; Xinge You; Ziqi Zhu; Weiyong Xue; Shujian Yu; Xiubao Jiang (SMC, 2015)

Human Heart Rate Estimation Using Ordinary Cameras under Natural Movement. - Shujian Yu; Xinge You; Xiubao Jiang; Kexin Zhao; Yi Mou; Weihua Ou; Yuanyan Tang; C. L. Philip Chen (SMC, 2015)

Multiple adaptive kernel size KLMS for Beijing PM2.5 prediction. - Zheng Cao; Shujian Yu; Guibiao Xu; Badong Chen; José C. Príncipe (IJCNN, 2016)

Improved functional link artificial neural network via convex combination for nonlinear active noise control. - Haiquan Zhao 001; Xiangping Zeng; Zhengyou He; Shujian Yu; Badong Chen (Appl. Soft Comput., 2016)

Multi-view non-negative matrix factorization by patch alignment framework with view consistency. - Weihua Ou; Shujian Yu; Gai Li; Jian Lu; Kesheng Zhang; Gang Xie (Neurocomputing, 2016)

STFT-like time frequency representations of nonstationary signal with arbitrary sampling schemes. - Shujian Yu; Xinge You; Weihua Ou; Xiubao Jiang; Kexin Zhao; Ziqi Zhu; Yi Mou; Xinyi Zhao (Neurocomputing, 2016)

Dynamic texture modeling and synthesis using multi-kernel Gaussian process dynamic model. - Ziqi Zhu; Xinge You; Shujian Yu; Jixin Zou; Haiquan Zhao 001 (Signal Process., 2016)

Kernel Learning for Dynamic Texture Synthesis. - Xinge You; Weigang Guo; Shujian Yu; Kan Li 002; José C. Príncipe; Dacheng Tao (IEEE Trans. Image Process., 2016)

Robust linear discriminant analysis with a Laplacian assumption on projection distribution. - Shujian Yu; Zheng Cao; Xiubao Jiang (ICASSP, 2017)

Autoencoders trained with relevant information: Blending Shannon and Wiener's perspectives. - Shujian Yu; Matthew Emigh; Eder Santana; José C. Príncipe (ICASSP, 2017)

Concept Drift Detection with Hierarchical Hypothesis Testing. - Shujian Yu; Zubin Abraham (SDM, 2017)

Marine Animal Classification with Correntropy Loss Based Multi-view Learning. - Zheng Cao; Shujian Yu; Bing Ouyang; Fraser R. Dalgleish; Anni K. Vuorenkoski; Gabriel Alsenas; José C. Príncipe (CoRR, 2017)

Concept Drift Detection and Adaptation with Hierarchical Hypothesis Testing. - Shujian Yu; Zubin Abraham; Heng Wang; Mohak Shah; José C. Príncipe (CoRR, 2017)

Joint Image Segmentation and Classification with Application to Cluttered Coral Images. - Ying Ma; Bing Ouyang; Stephanie Farrington; Shujian Yu; John Reed; José C. Príncipe (GlobalSIP, 2018)

Request-and-Reverify: Hierarchical Hypothesis Testing for Concept Drift Detection with Expensive Labels. - Shujian Yu; Xiaoyang Wang; José C. Príncipe (IJCAI, 2018)

Understanding Convolutional Neural Network Training with Information Theory. - Shujian Yu; Robert Jenssen; José C. Príncipe (CoRR, 2018)

Multi-view Hybrid Embedding: A Divide-and-Conquer Approach. - Jiamiao Xu; Shujian Yu; Xinge You; Mengjun Leng; Xiao-Yuan Jing; C. L. Philip Chen (CoRR, 2018)

Coarse-to-Fine Salient Object Detection with Low-Rank Matrix Recovery. - Qi Zheng 003; Shujian Yu; Xinge You; Qinmu Peng; Wei Yuan 001 (CoRR, 2018)

Multivariate Extension of Matrix-based Renyi's α-order Entropy Functional. - Shujian Yu; Luis Gonzalo Sánchez Giraldo; Robert Jenssen; José C. Príncipe (CoRR, 2018)

Co-regularized multiview nonnegative matrix factorization with correlation constraint for representation learning. - Weihua Ou; Fei Long; Yi Tan; Shujian Yu; Pengpeng Wang (Multim. Tools Appl., 2018)

Multi-view manifold learning with locality alignment. - Yue Zhao; Xinge You; Shujian Yu; Chang Xu 002; Wei Yuan 001; Xiao-Yuan Jing; Taiping Zhang; Dacheng Tao (Pattern Recognit., 2018)

Data Encryption Transmission and Authentication Scheme Based on Blockchain Technology. - Liugfen Li; Guowei Lin; Zouyu Xie; Shujian Yu; Zhen Guo; Yufang Liang (DPTA, 2019)

Closed-Loop Adaptation for Weakly-Supervised Semantic Segmentation. - Zhengqiang Zhang; Shujian Yu; Shi Yin; Qinmu Peng; Xinge You (CoRR, 2019)

Multiscale Principle of Relevant Information for Hyperspectral Image Classification. - Yantao Wei; Shujian Yu; José C. Príncipe (CoRR, 2019)

Information Plane Analysis of Deep Neural Networks via Matrix-Based Renyi's Entropy and Tensor Kernels. - Kristoffer Wickstrøm; Sigurd Løkse; Michael Kampffmeyer; Shujian Yu; José C. Príncipe; Robert Jenssen (CoRR, 2019)

Simple Stopping Criteria for Information Theoretic Feature Selection. - Shujian Yu; José C. Príncipe (Entropy, 2019)

Concept drift detection and adaptation with hierarchical hypothesis testing. - Shujian Yu; Zubin Abraham; Heng Wang; Mohak Shah; Yantao Wei; José C. Príncipe (J. Frankl. Inst., 2019)

Understanding autoencoders with information theoretic concepts. - Shujian Yu; José C. Príncipe (Neural Networks, 2019)

Robust Visual Tracking Using Multi-Frame Multi-Feature Joint Modeling. - Peng Zhang 040; Shujian Yu; Jiamiao Xu; Xinge You; Xiubao Jiang; Xiao-Yuan Jing; Dacheng Tao (IEEE Trans. Circuits Syst. Video Technol., 2019)

Composite Dynamic Texture Synthesis Using Hierarchical Linear Dynamical System. - Rishabh Singh; Shujian Yu; José C. Príncipe (ICASSP, 2020)

Measuring the Discrepancy between Conditional Distributions: Methods, Properties and Applications. - Shujian Yu; Ammar Shaker; Francesco Alesiani; José C. Príncipe (IJCAI, 2020)

Online Meta-Forest for Regression Data Streams. - Ammar Shaker; Christoph Gärtner; Xiao He; Shujian Yu (IJCNN, 2020)

Towards Interpretable Multi-task Learning Using Bilevel Programming. - Francesco Alesiani; Shujian Yu; Ammar Shaker; Wenzhe Yin (ECML/PKDD (2), 2020)

PRI-VAE: Principle-of-Relevant-Information Variational Autoencoders. - Yanjun Li 005; Shujian Yu; José C. Príncipe; Xiaolin Li 001; Dapeng Oliver Wu (CoRR, 2020)

Mutual Information Matrix for Interpretable Fault Detection. - Feiya Lv; Shujian Yu; Chenglin Wen; José C. Príncipe (CoRR, 2020)

Learning an Interpretable Graph Structure in Multi-Task Learning. - Shujian Yu; Francesco Alesiani; Ammar Shaker; Wenzhe Yin (CoRR, 2020)

Coarse-to-fine salient object detection with low-rank matrix recovery. - Qi Zheng 003; Shujian Yu; Xinge You (Neurocomputing, 2020)

On Kernel Method-Based Connectionist Models and Supervised Deep Learning Without Backpropagation. - Shiyu Duan; Shujian Yu; Yunmei Chen; José C. Príncipe (Neural Comput., 2020)

Multivariate Extension of Matrix-Based Rényi's $ alpha$α-Order Entropy Functional. - Shujian Yu; Luis Gonzalo Sánchez Giraldo; Robert Jenssen; José C. Príncipe (IEEE Trans. Pattern Anal. Mach. Intell., 2020)

Multiview Hybrid Embedding: A Divide-and-Conquer Approach. - Jiamiao Xu; Shujian Yu; Xinge You; Mengjun Leng; Xiao-Yuan Jing; C. L. Philip Chen (IEEE Trans. Cybern., 2020)

Measuring Dependence with Matrix-based Entropy Functional. - Shujian Yu; Francesco Alesiani; Xi Yu; Robert Jenssen; José C. Príncipe (AAAI, 2021)

Deep Deterministic Information Bottleneck with Matrix-Based Entropy Functional. - Xi Yu; Shujian Yu; José C. Príncipe (ICASSP, 2021)

Information-Theoretic Methods in Deep Neural Networks: Recent Advances and Emerging Opportunities. - Shujian Yu; Luis G. Sánchez Giraldo; José C. Príncipe (IJCAI, 2021)

Bilevel Continual Learning. - Ammar Shaker; Francesco Alesiani; Shujian Yu; Wenzhe Yin (IJCNN, 2021)

Learning to Transfer with von Neumann Conditional Divergence. - Ammar Shaker; Shujian Yu (CoRR, 2021)

Information Theoretic Structured Generative Modeling. - Bo Hu; Shujian Yu; José C. Príncipe (CoRR, 2021)

Computationally Efficient Approximations for Matrix-based Renyi's Entropy. - Tieliang Gong; Yuxin Dong; Shujian Yu; Hong Chen 004; Bo Dong 001; Chen Li 011; Qinghua Zheng (CoRR, 2021)

Interpretable fault detection using projections of mutual information matrix. - Feiya Lv; Shujian Yu; Chenglin Wen; José C. Príncipe (J. Frankl. Inst., 2021)

Understanding Convolutional Neural Networks With Information Theory: An Initial Exploration. - Shujian Yu; Kristoffer Wickstrøm; Robert Jenssen; José C. Príncipe (IEEE Trans. Neural Networks Learn. Syst., 2021)

Learning to Transfer with von Neumann Conditional Divergence. - Ammar Shaker; Shujian Yu; Daniel Oñoro-Rubio (AAAI, 2022)

Deep Deterministic Independent Component Analysis for Hyperspectral Unmixing. - Hongming Li; Shujian Yu; José C. Príncipe (ICASSP, 2022)

Multi-View Information Bottleneck Without Variational Approximation. - Qi Zhang 089; Shujian Yu; Jingmin Xin; Badong Chen (ICASSP, 2022)

Modular-Relatedness for Continual Learning. - Ammar Shaker; Francesco Alesiani; Shujian Yu (IDA, 2022)

Adversarial Training for the Adversarial Robustness of EEG-Based Brain-Computer Interfaces. - Yunhuan Li; Xi Yu; Shujian Yu; Badong Chen (MLSP, 2022)

Principle of relevant information for graph sparsification. - Shujian Yu; Francesco Alesiani; Wenzhe Yin; Robert Jenssen; José C. Príncipe (UAI, 2022)

Information-Theoretic Hashing for Zero-Shot Cross-Modal Retrieval. - Yufeng Shi; Shujian Yu; Duanquan Xu; Xinge You (CoRR, 2022)

Causality detection with matrix-based transfer entropy. - Wanqi Zhou; Shujian Yu; Badong Chen (Inf. Sci., 2022)

Modularizing Deep Learning via Pairwise Learning With Kernels. - Shiyu Duan; Shujian Yu; José C. Príncipe (IEEE Trans. Neural Networks Learn. Syst., 2022)

Computationally Efficient Approximations for Matrix-Based Rényi's Entropy. - Tieliang Gong; Yuxin Dong; Shujian Yu; Bo Dong 001 (IEEE Trans. Signal Process., 2022)

Functional Connectome of the Human Brain with Total Correlation. - Qiang Li 046; Greg Ver Steeg; Shujian Yu; Jesus Malo (Entropy, 2022)

Robust and Fast Measure of Information via Low-Rank Representation. - Yuxin Dong; Tieliang Gong; Shujian Yu; Hong Chen 004; Chen Li 011 (AAAI, 2023)

Causal Recurrent Variational Autoencoder for Medical Time Series Generation. - Hongming Li; Shujian Yu; José C. Príncipe (AAAI, 2023)

The Analysis of Deep Neural Networks by Information Theory: From Explainability to Generalization. - Shujian Yu (AAAI, 2023)

Revisiting the Robustness of the Minimum Error Entropy Criterion: A Transfer Learning Case Study. - Luis Pedro Silvestrin; Shujian Yu; Mark Hoogendoorn (ECAI, 2023)

Higher-Order Organization in the Human Brain From Matrix-Based Rényi's Entropy. - Qiang Li 046; Shujian Yu; Kristoffer H. Madsen; Vince D. Calhoun; Armin Iraji (ICASSP Workshops, 2023)

Towards a More Stable and General Subgraph Information Bottleneck. - Hongzhi Liu; Kaizhong Zheng; Shujian Yu; Badong Chen (ICASSP, 2023)

Sequential Invariant Information Bottleneck. - Yichen Zhang; Shujian Yu; Badong Chen (ICASSP, 2023)

Identification of Predictive Subnetwork for Brain Network-Based Psychiatric Diagnosis: An Information-Theoretic Perspective. - Kaizhong Zheng; Shujian Yu; Badong Chen (ICASSP Workshops, 2023)

Continual Invariant Risk Minimization. - Francesco Alesiani; Shujian Yu; Mathias Niepert (CoRR, 2023)

MIMIR: Masked Image Modeling for Mutual Information-based Adversarial Robustness. - Xiaoyun Xu; Shujian Yu; Jingzheng Wu; Stjepan Picek (CoRR, 2023)

Gated information bottleneck for generalization in sequential environments. - Francesco Alesiani; Shujian Yu; Xi Yu (Knowl. Inf. Syst., 2023)

Multiscale principle of relevant information for hyperspectral image classification. - Yantao Wei; Shujian Yu; Luis G. Sánchez Giraldo; José C. Príncipe (Mach. Learn., 2023)

Analysis of Deep Convolutional Neural Networks Using Tensor Kernels and Matrix-Based Entropy. - Kristoffer K. Wickstrøm; Sigurd Løkse; Michael C. Kampffmeyer; Shujian Yu; José C. Príncipe; Robert Jenssen (Entropy, 2023)

Optimal Randomized Approximations for Matrix-Based Rényi's Entropy. - Yuxin Dong; Tieliang Gong; Shujian Yu; Chen Li 011 (IEEE Trans. Inf. Theory, 2023)

Selective Imputation for Multivariate Time Series Datasets With Missing Values. - Ane Blázquez-García; Kristoffer Wickstrøm; Shujian Yu; Karl Øyvind Mikalsen; Ahcène Boubekki; Angel Conde; Usue Mori; Robert Jenssen; José Antonio Lozano 001 (IEEE Trans. Knowl. Data Eng., 2023)

A Componentwise Approach to Weakly Supervised Semantic Segmentation Using Dual-Feedback Network. - Zhengqiang Zhang; Qinmu Peng; Sichao Fu; Wenjie Wang; Yiu-Ming Cheung; Yue Zhao; Shujian Yu; Xinge You (IEEE Trans. Neural Networks Learn. Syst., 2023)

Coping with change: Learning invariant and minimum sufficient representations for fine-grained visual categorization. - Shuo Ye; Shujian Yu; Wenjin Hou; Yu Wang; Xinge You (Comput. Vis. Image Underst., 2023)

DIB-X: Formulating Explainability Principles for a Self-Explainable Model Through Information Theoretic Learning. - Changkyu Choi; Shujian Yu; Michael Kampffmeyer; Arnt-Børre Salberg; Nils Olav Handegard; Robert Jenssen (ICASSP, 2024)

Rethinking Information-theoretic Generalization: Loss Entropy Induced PAC Bounds. - Yuxin Dong; Tieliang Gong; Hong Chen 004; Shujian Yu; Chen Li 011 (ICLR, 2024)

Cauchy-Schwarz Divergence Information Bottleneck for Regression. - Shujian Yu; Xi Yu; Sigurd Løkse; Robert Jenssen; José C. Príncipe (ICLR, 2024)

Jacobian Regularizer-based Neural Granger Causality. - Wanqi Zhou; Shuanghao Bai; Shujian Yu; Qibin Zhao; Badong Chen (ICML, 2024)

BAN: Detecting Backdoors Activated by Adversarial Neuron Noise. - Xiaoyun Xu; Zhuoran Liu 001; Stefanos Koffas; Shujian Yu; Stjepan Picek (NeurIPS, 2024)

Domain Adaptation with Cauchy-Schwarz Divergence. - Wenzhe Yin; Shujian Yu; Yicong Lin; Jie Liu 043; Jan-Jakob Sonke; Efstratios Gavves (UAI, 2024)

Generalized Cauchy-Schwarz Divergence and Its Deep Learning Applications. - Mingfei Lu; Shujian Yu; Robert Jenssen; Badong Chen (CoRR, 2024)

Domain Adaptation with Cauchy-Schwarz Divergence. - Wenzhe Yin; Shujian Yu; Yicong Lin; Jie Li 001; Jan-Jakob Sonke; Efstratios Gavves (CoRR, 2024)

ELEMENT: Episodic and Lifelong Exploration via Maximum Entropy. - Hongming Li; Shujian Yu; Bin Liu; José C. Príncipe (CoRR, 2024)

Discovering common information in multi-view data. - Qi Zhang 089; Mingfei Lu; Shujian Yu; Jingmin Xin; Badong Chen (Inf. Fusion, 2024)

R2-trans: Fine-grained visual categorization with redundancy reduction. - Shuo Ye; Shujian Yu; Yu Wang; Xinge You (Image Vis. Comput., 2024)

Incipient fault detection and isolation with Cauchy-Schwarz divergence: A probabilistic approach. - Feiya Lv; Shujian Yu; Huawei Ye; Jinsong Zhao; Chenglin Wen (J. Frankl. Inst., 2024)

BPI-GNN: Interpretable brain network-based psychiatric diagnosis and subtyping. - Kaizhong Zheng; Shujian Yu; Liangjun Chen; Lujuan Dang; Badong Chen (NeuroImage, 2024)

CI-GNN: A Granger causality-inspired graph neural network for interpretable brain network-based psychiatric diagnosis. - Kaizhong Zheng; Shujian Yu; Badong Chen (Neural Networks, 2024)

Cauchy-Schwarz Divergence Transfer Entropy. - Zhaozhao Ma; Shujian Yu (ICASSP, 2025)

A Hierarchical Taxonomy For Deep State Space Models. - Shiqin Tang; Pengxing Feng; Shujian Yu; Yining Dong; S. Joe Qin (ICASSP, 2025)

Deep Dynamic Probabilistic Canonical Correlation Analysis. - Shiqin Tang; Shujian Yu; Yining Dong; S. Joe Qin (ICASSP, 2025)

Start Smart: Leveraging Gradients For Enhancing Mask-based XAI Methods. - Buelent Uendes; Shujian Yu; Mark Hoogendoorn (ICLR, 2025)

InfoDPCCA: Information-Theoretic Dynamic Probabilistic Canonical Correlation Analysis. - Shiqin Tang; Shujian Yu (UAI, 2025)

A unified model integrating Granger causality-based causal discovery and fault diagnosis in chemical processes. - Feiya Lv; Borui Yang; Shujian Yu; Shengwu Zou; Xiaolin Wang; Jinsong Zhao; Chenglin Wen (Comput. Chem. Eng., 2025)

Generalized Cauchy-Schwarz divergence: Efficient estimation and applications in deep learning. - Mingfei Lu; Shujian Yu; Robert Jenssen; Badong Chen (Neurocomputing, 2025)

An information bottleneck approach for feature selection. - Qi Zhang 089; Mingfei Lu; Shujian Yu; Jingmin Xin; Badong Chen (Pattern Recognit., 2025)

Towards the Generalization of Multi-view Learning: An Information-theoretical Analysis. - Wen Wen; Tieliang Gong; Yuxin Dong; Shujian Yu; Weizhan Zhang (CoRR, 2025)

Distributional Vision-Language Alignment by Cauchy-Schwarz Divergence. - Wenzhe Yin; Zehao Xiao; Pan Zhou; Shujian Yu; Jiayi Shen; Jan-Jakob Sonke; Efstratios Gavves (CoRR, 2025)

Guest Editorial: Special Issue on Information Theoretic Methods for the Generalization, Robustness, and Interpretability of Machine Learning. - Badong Chen; Shujian Yu; Robert Jenssen; José C. Príncipe; Klaus-Robert Müller (IEEE Trans. Neural Networks Learn. Syst., 2025)

Aggregation of Dependent Expert Distributions in Multimodal Variational Autoencoders. - Rogelio Andrade Mancisidor; Robert Jenssen; Shujian Yu; Michael Kampffmeyer (CoRR, 2025)

MvHo-IB: Multi-View Higher-Order Information Bottleneck for Brain Disorder Diagnosis. - Kunyu Zhang; Qiang Li 046; Shujian Yu (CoRR, 2025)

Dual-Alignment Knowledge Retention for Continual Medical Image Segmentation. - Yuxin Ye; Yan Liu; Shujian Yu (CoRR, 2025)

When Brain Foundation Model Meets Cauchy-Schwarz Divergence: A New Framework for Cross-Subject Motor Imagery Decoding. - Jinzhou Wu; Baoping Tang; Qikang Li; Yi Wang; Cheng Li; Shujian Yu (CoRR, 2025)

The Conditional Cauchy-Schwarz Divergence With Applications to Time-Series Data and Sequential Decision Making. - Shujian Yu; Hongming Li; Sigurd Løkse; Robert Jenssen; José C. Príncipe (IEEE Trans. Pattern Anal. Mach. Intell., 2025)

BrainIB: Interpretable Brain Network-Based Psychiatric Diagnosis With Graph Information Bottleneck. - Kaizhong Zheng; Shujian Yu; Baojuan Li; Robert Jenssen; Badong Chen (IEEE Trans. Neural Networks Learn. Syst., 2025)