Shujian Yu
20 papers · 2018–2026 · 8 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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🗺️ Taxonomy Completionist (48) 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Bronze 🏆 Grand Slam
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Keyword Champion
(2)
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Triple Crown
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Keyword Collector
(108)
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Unstoppable · Bronze
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Prolific Year · Productive
💎
Century Club · Bronze
Top co-authors
Research topics
Machine Learning
(14)
Artificial Intelligence
(10)
Core AI
(9)
Deep Learning
(8)
Optimization & Theory
(8)
Core Methods
(6)
Mathematics & Optimization
(5)
Learning Types · Deep Learning
(4)
Learning Types · Machine Learning
(4)
Mathematics
(4)
Models
(4)
Healthcare & Medicine
(3)
Clinical
(3)
Application Areas
(2)
Optimization
(2)
Keywords
information theory
(4)
mutual information
(4)
representation learning
(3)
variational autoencoder
(3)
catastrophic forgetting
(2)
conditional distribution
(2)
deep neural network
(2)
information bottleneck
(2)
concept drift detection
(2)
variational inference
(2)
active learning
(1)
continual learning
(1)
multi-task learning
(1)
adversarial robustness
(1)
causal inference
(1)
functional connectivity
(1)
learning theory
(1)
transfer learning
(1)
unsupervised learning
(1)
graph laplacian
(1)
Papers
Continual Learning for fMRI-Based Brain Disorder Diagnosis via Functional Connectivity Matrices Generative Replay
CVPR 2026
Particle Dynamics for Latent-Variable Energy-Based Models
UAI 2026
Aggregation of Dependent Expert Distributions in Multimodal Variational Autoencoders
ICML 2025
InfoDPCCA: Information-Theoretic Dynamic Probabilistic Canonical Correlation Analysis
UAI 2025
MvHo-IB: Multi-View Higher-Order Information Bottleneck for Brain Disorder Diagnosis
MICCAI 2025
Start Smart: Leveraging Gradients For Enhancing Mask-based XAI Methods
ICLR 2025
BAN: Detecting Backdoors Activated by Adversarial Neuron Noise
NeurIPS 2024
Cauchy-Schwarz Divergence Information Bottleneck for Regression
ICLR 2024
Domain Adaptation with Cauchy-Schwarz Divergence
UAI 2024
Jacobian Regularizer-based Neural Granger Causality
ICML 2024
Rethinking Information-theoretic Generalization: Loss Entropy Induced PAC Bounds
ICLR 2024
Causal Recurrent Variational Autoencoder for Medical Time Series Generation
AAAI 2023
Robust and Fast Measure of Information via Low-Rank Representation
AAAI 2023
The Analysis of Deep Neural Networks by Information Theory: From Explainability to Generalization
AAAI 2023
Learning to Transfer with von Neumann Conditional Divergence
AAAI 2022
Principle of relevant information for graph sparsification
UAI 2022
Information-Theoretic Methods in Deep Neural Networks: Recent Advances and Emerging Opportunities
IJCAI 2021
Measuring Dependence with Matrix-based Entropy Functional
AAAI 2021
Measuring the Discrepancy between Conditional Distributions: Methods, Properties and Applications
IJCAI 2020
Request-and-Reverify: Hierarchical Hypothesis Testing for Concept Drift Detection with Expensive Labels
IJCAI 2018