Shujian Yu

ORCID

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 114

Top Venues

Publications

Mingfei Lu, Shujian Yu, Robert Jenssen, Badong Chen
Generalized Cauchy-Schwarz Divergence and Its Deep Learning Applications. CoRR (2024)
Shujian Yu, Xi Yu, Sigurd Løkse, Robert Jenssen, José C. Príncipe
Cauchy-Schwarz Divergence Information Bottleneck for Regression. ICLR (2024)
Qi Zhang, Mingfei Lu, Shujian Yu, Jingmin Xin, Badong Chen
Discovering Common Information in Multi-view Data. CoRR (2024)
Shujian Yu, Xi Yu, Sigurd Løkse, Robert Jenssen, José C. Príncipe
Cauchy-Schwarz Divergence Information Bottleneck for Regression. CoRR (2024)
Qi Zhang, Mingfei Lu, Shujian Yu, Jingmin Xin, Badong Chen
Discovering common information in multi-view data. Inf. Fusion 108 (2024)
Kaizhong Zheng, Shujian Yu, Badong Chen
CI-GNN: A Granger causality-inspired graph neural network for interpretable brain network-based psychiatric diagnosis. Neural Networks 172 (2024)
Xiaoyun Xu, Zhuoran Liu, Stefanos Koffas, Shujian Yu, Stjepan Picek
BAN: Detecting Backdoors Activated by Adversarial Neuron Noise. CoRR (2024)
Changkyu Choi, Shujian Yu, Michael Kampffmeyer, Arnt-Børre Salberg, Nils Olav Handegard, Robert Jenssen
DIB-X: Formulating Explainability Principles for a Self-Explainable Model Through Information Theoretic Learning. ICASSP (2024)
Yuxin Dong, Tieliang Gong, Hong Chen, Shujian Yu, Chen Li
Rethinking Information-theoretic Generalization: Loss Entropy Induced PAC Bounds. ICLR (2024)
Shuo Ye, Shujian Yu, Yu Wang, Xinge You
R2-trans: Fine-grained visual categorization with redundancy reduction. Image Vis. Comput. 143 (2024)
Kaizhong Zheng, Shujian Yu, Liangjun Chen, Lujuan Dang, Badong Chen
BPI-GNN: Interpretable brain network-based psychiatric diagnosis and subtyping. NeuroImage 292 (2024)
Wanqi Zhou, Shuanghao Bai, Shujian Yu, Qibin Zhao, Badong Chen
Jacobian Regularizer-based Neural Granger Causality. CoRR (2024)
Wenzhe Yin, Shujian Yu, Yicong Lin, Jie Li, Jan-Jakob Sonke, Efstratios Gavves
Domain Adaptation with Cauchy-Schwarz Divergence. CoRR (2024)
Luis Pedro Silvestrin, Shujian Yu, Mark Hoogendoorn
Revisiting the Robustness of the Minimum Error Entropy Criterion: A Transfer Learning Case Study. ECAI (2023)
Luis Pedro Silvestrin, Shujian Yu, Mark Hoogendoorn
Revisiting the Robustness of the Minimum Error Entropy Criterion: A Transfer Learning Case Study. CoRR (2023)
Kaizhong Zheng, Shujian Yu, Badong Chen
Identification of Predictive Subnetwork for Brain Network-Based Psychiatric Diagnosis: An Information-Theoretic Perspective. ICASSP Workshops (2023)
Qiang Li, Shujian Yu, Kristoffer H. Madsen, Vince D. Calhoun, Armin Iraji
Higher-Order Organization in the Human Brain From Matrix-Based Rényi's Entropy. ICASSP Workshops (2023)
Shujian Yu, Hongming Li, Sigurd Løkse, Robert Jenssen, José C. Príncipe
The Conditional Cauchy-Schwarz Divergence with Applications to Time-Series Data and Sequential Decision Making. CoRR (2023)
Shujian Yu
The Analysis of Deep Neural Networks by Information Theory: From Explainability to Generalization. AAAI (2023)
Xiaoyun Xu, Shujian Yu, Jingzheng Wu, Stjepan Picek
MIMIR: Masked Image Modeling for Mutual Information-based Adversarial Robustness. CoRR (2023)
Hongming Li, Shujian Yu, José C. Príncipe
Causal Recurrent Variational Autoencoder for Medical Time Series Generation. AAAI (2023)
Yuxin Dong, Tieliang Gong, Shujian Yu, Chen Li
Optimal Randomized Approximations for Matrix-Based Rényi's Entropy. IEEE Trans. Inf. Theory 69 (7) (2023)
Kristoffer K. Wickstrøm, Sigurd Løkse, Michael C. Kampffmeyer, Shujian Yu, José C. Príncipe, Robert Jenssen
Analysis of Deep Convolutional Neural Networks Using Tensor Kernels and Matrix-Based Entropy. Entropy 25 (6) (2023)
Shuo Ye, Shujian Yu, Wenjin Hou, Yu Wang, Xinge You
Coping with Change: Learning Invariant and Minimum Sufficient Representations for Fine-Grained Visual Categorization. CoRR (2023)
Hongzhi Liu, Kaizhong Zheng, Shujian Yu, Badong Chen
Towards a More Stable and General Subgraph Information Bottleneck. ICASSP (2023)
Yuxin Dong, Tieliang Gong, Shujian Yu, Hong Chen, Chen Li
Robust and Fast Measure of Information via Low-Rank Representation. AAAI (2023)
Zhengqiang Zhang, Qinmu Peng, Sichao Fu, Wenjie Wang, Yiu-Ming Cheung, Yue Zhao, Shujian Yu, Xinge You
A Componentwise Approach to Weakly Supervised Semantic Segmentation Using Dual-Feedback Network. IEEE Trans. Neural Networks Learn. Syst. 34 (10) (2023)
Hongming Li, Shujian Yu, José C. Príncipe
Causal Recurrent Variational Autoencoder for Medical Time Series Generation. CoRR (2023)
Kaizhong Zheng, Shujian Yu, Badong Chen
CI-GNN: A Granger Causality-Inspired Graph Neural Network for Interpretable Brain Network-Based Psychiatric Diagnosis. CoRR (2023)
Yantao Wei, Shujian Yu, Luis G. Sánchez Giraldo, José C. Príncipe
Multiscale principle of relevant information for hyperspectral image classification. Mach. Learn. 112 (4) (2023)
Shuo Ye, Shujian Yu, Wenjin Hou, Yu Wang, Xinge You
Coping with change: Learning invariant and minimum sufficient representations for fine-grained visual categorization. Comput. Vis. Image Underst. 237 (2023)
Francesco Alesiani, Shujian Yu, Mathias Niepert
Continual Invariant Risk Minimization. CoRR (2023)
Yichen Zhang, Shujian Yu, Badong Chen
Sequential Invariant Information Bottleneck. ICASSP (2023)
Qiang Li, Shujian Yu, Kristoffer H. Madsen, Vince D. Calhoun, Armin Iraji
Higher-order Organization in the Human Brain from Matrix-Based Rényi's Entropy. CoRR (2023)
Francesco Alesiani, Shujian Yu, Xi Yu
Gated information bottleneck for generalization in sequential environments. Knowl. Inf. Syst. 65 (2) (2023)
Ane Blázquez-García, Kristoffer Wickstrøm, Shujian Yu, Karl Øyvind Mikalsen, Ahcène Boubekki, Angel Conde, Usue Mori, Robert Jenssen, José Antonio Lozano
Selective Imputation for Multivariate Time Series Datasets With Missing Values. IEEE Trans. Knowl. Data Eng. 35 (9) (2023)
Ammar Shaker, Shujian Yu, Daniel Oñoro-Rubio
Learning to Transfer with von Neumann Conditional Divergence. AAAI (2022)
Yuxin Dong, Tieliang Gong, Shujian Yu, Hong Chen, Chen Li
Robust and Fast Measure of Information via Low-rank Representation. CoRR (2022)
Wanqi Zhou, Shujian Yu, Badong Chen
Causality detection with matrix-based transfer entropy. Inf. Sci. 613 (2022)
Kaizhong Zheng, Shujian Yu, Baojuan Li, Robert Jenssen, Badong Chen
BrainIB: Interpretable Brain Network-based Psychiatric Diagnosis with Graph Information Bottleneck. CoRR (2022)
Qi Zhang, Shujian Yu, Jingmin Xin, Badong Chen
Multi-View Information Bottleneck Without Variational Approximation. ICASSP (2022)
Qiang Li, Greg Ver Steeg, Shujian Yu, Jesus Malo
Functional Connectome of the Human Brain with Total Correlation. Entropy 24 (12) (2022)
Ammar Shaker, Francesco Alesiani, Shujian Yu
Modular-Relatedness for Continual Learning. IDA (2022)
Hongming Li, Shujian Yu, José C. Príncipe
Deep Deterministic Independent Component Analysis for Hyperspectral Unmixing. ICASSP (2022)
Yuxin Dong, Tieliang Gong, Shujian Yu, Chen Li
Optimal Randomized Approximations for Matrix based Renyi's Entropy. CoRR (2022)
Qi Zhang, Shujian Yu, Jingmin Xin, Badong Chen
Multi-view Information Bottleneck Without Variational Approximation. CoRR (2022)
Shiyu Duan, Shujian Yu, José C. Príncipe
Modularizing Deep Learning via Pairwise Learning With Kernels. IEEE Trans. Neural Networks Learn. Syst. 33 (4) (2022)
Yufeng Shi, Shujian Yu, Duanquan Xu, Xinge You
Information-Theoretic Hashing for Zero-Shot Cross-Modal Retrieval. CoRR (2022)
Tieliang Gong, Yuxin Dong, Shujian Yu, Bo Dong
Computationally Efficient Approximations for Matrix-Based Rényi's Entropy. IEEE Trans. Signal Process. 70 (2022)
Yu Wang, Shuo Ye, Shujian Yu, Xinge You
R2-Trans: Fine-Grained Visual Categorization with Redundancy Reduction. CoRR (2022)
Hongming Li, Shujian Yu, José C. Principe
Deep Deterministic Independent Component Analysis for Hyperspectral Unmixing. CoRR (2022)
Shujian Yu, Francesco Alesiani, Wenzhe Yin, Robert Jenssen, José C. Príncipe
Principle of relevant information for graph sparsification. UAI (2022)
Shujian Yu, Francesco Alesiani, Wenzhe Yin, Robert Jenssen, José C. Príncipe
Principle of Relevant Information for Graph Sparsification. CoRR (2022)
Yunhuan Li, Xi Yu, Shujian Yu, Badong Chen
Adversarial Training for the Adversarial Robustness of EEG-Based Brain-Computer Interfaces. MLSP (2022)
Bo Hu, Shujian Yu, José C. Príncipe
Information Theoretic Structured Generative Modeling. CoRR (2021)
Xi Yu, Shujian Yu, José C. Príncipe
Deep Deterministic Information Bottleneck with Matrix-Based Entropy Functional. ICASSP (2021)
Shujian Yu, Kristoffer Wickstrøm, Robert Jenssen, José C. Príncipe
Understanding Convolutional Neural Networks With Information Theory: An Initial Exploration. IEEE Trans. Neural Networks Learn. Syst. 32 (1) (2021)
Shujian Yu, Francesco Alesiani, Xi Yu, Robert Jenssen, José C. Príncipe
Measuring Dependence with Matrix-based Entropy Functional. AAAI (2021)
Francesco Alesiani, Shujian Yu, Xi Yu
Gated Information Bottleneck for Generalization in Sequential Environments. ICDM (2021)
Francesco Alesiani, Shujian Yu, Xi Yu
Gated Information Bottleneck for Generalization in Sequential Environments. CoRR (2021)
Xi Yu, Shujian Yu, José C. Príncipe
Deep Deterministic Information Bottleneck with Matrix-based Entropy Functional. CoRR (2021)
Shujian Yu, Francesco Alesiani, Xi Yu, Robert Jenssen, José C. Príncipe
Measuring Dependence with Matrix-based Entropy Functional. CoRR (2021)
Feiya Lv, Shujian Yu, Chenglin Wen, José C. Príncipe
Interpretable fault detection using projections of mutual information matrix. J. Frankl. Inst. 358 (7) (2021)
Tieliang Gong, Yuxin Dong, Shujian Yu, Hong Chen, Bo Dong, Chen Li, Qinghua Zheng
Computationally Efficient Approximations for Matrix-based Renyi's Entropy. CoRR (2021)
Ammar Shaker, Shujian Yu
Learning to Transfer with von Neumann Conditional Divergence. CoRR (2021)
Ammar Shaker, Francesco Alesiani, Shujian Yu, Wenzhe Yin
Bilevel Continual Learning. IJCNN (2021)
Shujian Yu, Luis G. Sánchez Giraldo, José C. Príncipe
Information-Theoretic Methods in Deep Neural Networks: Recent Advances and Emerging Opportunities. IJCAI (2021)
Shujian Yu, Francesco Alesiani, Ammar Shaker, Wenzhe Yin
Learning an Interpretable Graph Structure in Multi-Task Learning. CoRR (2020)
Ammar Shaker, Christoph Gärtner, Xiao He, Shujian Yu
Online Meta-Forest for Regression Data Streams. IJCNN (2020)
Shujian Yu, Luis Gonzalo Sánchez Giraldo, Robert Jenssen, José C. Príncipe
Multivariate Extension of Matrix-Based Rényi's $\alpha$α-Order Entropy Functional. IEEE Trans. Pattern Anal. Mach. Intell. 42 (11) (2020)
Ammar Shaker, Shujian Yu, Francesco Alesiani
Modular-Relatedness for Continual Learning. CoRR (2020)
Rishabh Singh, Shujian Yu, José C. Príncipe
Composite Dynamic Texture Synthesis Using Hierarchical Linear Dynamical System. ICASSP (2020)
Feiya Lv, Shujian Yu, Chenglin Wen, José C. Príncipe
Mutual Information Matrix for Interpretable Fault Detection. CoRR (2020)
Francesco Alesiani, Shujian Yu, Ammar Shaker, Wenzhe Yin
Towards Interpretable Multi-Task Learning Using Bilevel Programming. CoRR (2020)
Shujian Yu, Ammar Shaker, Francesco Alesiani, José C. Príncipe
Measuring the Discrepancy between Conditional Distributions: Methods, Properties and Applications. IJCAI (2020)
Yanjun Li, Shujian Yu, José C. Príncipe, Xiaolin Li, Dapeng Oliver Wu
PRI-VAE: Principle-of-Relevant-Information Variational Autoencoders. CoRR (2020)
Shiyu Duan, Shujian Yu, Yunmei Chen, José C. Príncipe
On Kernel Method-Based Connectionist Models and Supervised Deep Learning Without Backpropagation. Neural Comput. 32 (1) (2020)
Ammar Shaker, Francesco Alesiani, Shujian Yu, Wenzhe Yin
Bilevel Continual Learning. CoRR (2020)
Qi Zheng, Shujian Yu, Xinge You
Coarse-to-fine salient object detection with low-rank matrix recovery. Neurocomputing 376 (2020)
Shujian Yu, Ammar Shaker, Francesco Alesiani, José C. Príncipe
Measuring the Discrepancy between Conditional Distributions: Methods, Properties and Applications. CoRR (2020)
Jiamiao Xu, Shujian Yu, Xinge You, Mengjun Leng, Xiao-Yuan Jing, C. L. Philip Chen
Multiview Hybrid Embedding: A Divide-and-Conquer Approach. IEEE Trans. Cybern. 50 (8) (2020)
Shiyu Duan, Shujian Yu, José C. Príncipe
Modularizing Deep Learning via Pairwise Learning With Kernels. CoRR (2020)
Francesco Alesiani, Shujian Yu, Ammar Shaker, Wenzhe Yin
Towards Interpretable Multi-task Learning Using Bilevel Programming. ECML/PKDD (2) (2020)
Liugfen Li, Guowei Lin, Zouyu Xie, Shujian Yu, Zhen Guo, Yufang Liang
Data Encryption Transmission and Authentication Scheme Based on Blockchain Technology. DPTA (2019)
Yantao Wei, Shujian Yu, José C. Príncipe
Multiscale Principle of Relevant Information for Hyperspectral Image Classification. CoRR (2019)
Shujian Yu, Zubin Abraham, Heng Wang, Mohak Shah, Yantao Wei, José C. Príncipe
Concept drift detection and adaptation with hierarchical hypothesis testing. J. Frankl. Inst. 356 (5) (2019)
Shujian Yu, José C. Príncipe
Understanding autoencoders with information theoretic concepts. Neural Networks 117 (2019)
Kristoffer Wickstrøm, Sigurd Løkse, Michael Kampffmeyer, Shujian Yu, José C. Príncipe, Robert Jenssen
Information Plane Analysis of Deep Neural Networks via Matrix-Based Renyi's Entropy and Tensor Kernels. CoRR (2019)
Shujian Yu, José C. Príncipe
Simple Stopping Criteria for Information Theoretic Feature Selection. Entropy 21 (1) (2019)
Zhengqiang Zhang, Shujian Yu, Shi Yin, Qinmu Peng, Xinge You
Closed-Loop Adaptation for Weakly-Supervised Semantic Segmentation. CoRR (2019)
Peng Zhang, Shujian Yu, Jiamiao Xu, Xinge You, Xiubao Jiang, Xiao-Yuan Jing, Dacheng Tao
Robust Visual Tracking Using Multi-Frame Multi-Feature Joint Modeling. IEEE Trans. Circuits Syst. Video Technol. 29 (12) (2019)
Shujian Yu, Xiaoyang Wang, José C. Príncipe
Request-and-Reverify: Hierarchical Hypothesis Testing for Concept Drift Detection with Expensive Labels. IJCAI (2018)
Shujian Yu, Luis Gonzalo Sánchez Giraldo, Robert Jenssen, José C. Príncipe
Multivariate Extension of Matrix-based Renyi's α-order Entropy Functional. CoRR (2018)
Peng Zhang, Shujian Yu, Jiamiao Xu, Xinge You, Xiubao Jiang, Xiao-Yuan Jing, Dacheng Tao
Robust Visual Tracking using Multi-Frame Multi-Feature Joint Modeling. CoRR (2018)
Shujian Yu, José C. Príncipe
Understanding Autoencoders with Information Theoretic Concepts. CoRR (2018)
Qi Zheng, Shujian Yu, Xinge You, Qinmu Peng, Wei Yuan
Coarse-to-Fine Salient Object Detection with Low-Rank Matrix Recovery. CoRR (2018)
Yue Zhao, Xinge You, Shujian Yu, Chang Xu, Wei Yuan, Xiao-Yuan Jing, Taiping Zhang, Dacheng Tao
Multi-view manifold learning with locality alignment. Pattern Recognit. 78 (2018)
Jiamiao Xu, Shujian Yu, Xinge You, Mengjun Leng, Xiao-Yuan Jing, C. L. Philip Chen
Multi-view Hybrid Embedding: A Divide-and-Conquer Approach. CoRR (2018)
Shujian Yu, José C. Príncipe
Simple stopping criteria for information theoretic feature selection. CoRR (2018)
Ying Ma, Bing Ouyang, Stephanie Farrington, Shujian Yu, John Reed, José C. Príncipe
Joint Image Segmentation and Classification with Application to Cluttered Coral Images. GlobalSIP (2018)

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Publication Activity (10 Years)

Top Topics

Top Venues

Shujian Yu