Yu, Shujian

21 publications

ICML 2025 Aggregation of Dependent Expert Distributions in Multimodal Variational Autoencoders Rogelio A. Mancisidor, Robert Jenssen, Shujian Yu, Michael Kampffmeyer
UAI 2025 InfoDPCCA: Information-Theoretic Dynamic Probabilistic Canonical Correlation Analysis Shiqin Tang, Shujian Yu
TMLR 2025 Learning Task-Aware Abstract Representations for Meta-Reinforcement Learning Louk van Remmerden, Zhao Yang, Shujian Yu, Mark Hoogendoorn, Vincent Francois-Lavet
ICLR 2025 Start Smart: Leveraging Gradients for Enhancing Mask-Based XAI Methods Buelent Uendes, Shujian Yu, Mark Hoogendoorn
NeurIPS 2024 BAN: Detecting Backdoors Activated by Adversarial Neuron Noise Xiaoyun Xu, Zhuoran Liu, Stefanos Koffas, Shujian Yu, Stjepan Picek
ICLR 2024 Cauchy-Schwarz Divergence Information Bottleneck for Regression Shujian Yu, Xi Yu, Sigurd Løkse, Robert Jenssen, Jose C Principe
UAI 2024 Domain Adaptation with Cauchy-Schwarz Divergence Wenzhe Yin, Shujian Yu, Yicong Lin, Jie Liu, Jan-Jakob Sonke, Efstratios Gavves
ICML 2024 Jacobian Regularizer-Based Neural Granger Causality Wanqi Zhou, Shuanghao Bai, Shujian Yu, Qibin Zhao, Badong Chen
ICLR 2024 Rethinking Information-Theoretic Generalization: Loss Entropy Induced PAC Bounds Yuxin Dong, Tieliang Gong, Hong Chen, Shujian Yu, Chen Li
NeurIPSW 2023 Aberrant High-Order Dependencies in Schizophrenia Resting-State Functional MRI Networks Qiang Li, Vince Calhoun, Adithya Ram Ballem, Shujian Yu, Jesus Malo, Armin Iraji
AAAI 2023 Causal Recurrent Variational Autoencoder for Medical Time Series Generation Hongming Li, Shujian Yu, José C. Príncipe
MLJ 2023 Multiscale Principle of Relevant Information for Hyperspectral Image Classification Yantao Wei, Shujian Yu, Luis G. Sánchez Giraldo, José C. Príncipe
AAAI 2023 Robust and Fast Measure of Information via Low-Rank Representation Yuxin Dong, Tieliang Gong, Shujian Yu, Hong Chen, Chen Li
AAAI 2023 The Analysis of Deep Neural Networks by Information Theory: From Explainability to Generalization Shujian Yu
AAAI 2022 Learning to Transfer with Von Neumann Conditional Divergence Ammar Shaker, Shujian Yu, Daniel Oñoro-Rubio
UAI 2022 Principle of Relevant Information for Graph Sparsification Shujian Yu, Francesco Alesiani, Wenzhe Yin, Robert Jenssen, Jose C. Principe
IJCAI 2021 Information-Theoretic Methods in Deep Neural Networks: Recent Advances and Emerging Opportunities Shujian Yu, Luis G. Sánchez Giraldo, José C. Príncipe
AAAI 2021 Measuring Dependence with Matrix-Based Entropy Functional Shujian Yu, Francesco Alesiani, Xi Yu, Robert Jenssen, José C. Príncipe
IJCAI 2020 Measuring the Discrepancy Between Conditional Distributions: Methods, Properties and Applications Shujian Yu, Ammar Shaker, Francesco Alesiani, José C. Príncipe
ECML-PKDD 2020 Towards Interpretable Multi-Task Learning Using Bilevel Programming Francesco Alesiani, Shujian Yu, Ammar Shaker, Wenzhe Yin
IJCAI 2018 Request-and-Reverify: Hierarchical Hypothesis Testing for Concept Drift Detection with Expensive Labels Shujian Yu, Xiaoyang Wang, José C. Príncipe