Shujian Yu
18 papers · 2018–2025 · 7 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (7) π Interdisciplinary Bridge π§ Keyword Pioneer π£ Hot Topic Early Bird π Academic Marathon (7)
π
Renaissance Researcher
(5)
πΊοΈ
Taxonomy Completionist
(37)
π
Conference Polyglot
(7)
π
Triple Crown
π
Grand Slam
π
Keyword Champion
(2)
π
Century Club
(18)
β‘
Prolific Year
(5)
ποΈ
Keyword Collector
(65)
π₯
Unstoppable
(6)
Conferences
AAAI (5)
ICLR (3)
IJCAI (3)
UAI (3)
ICML (2)
MICCAI (1)
NIPS (1)
Top co-authors
Keywords
information theory
(4)
concept drift detection
(2)
conditional distribution
(2)
mutual information
(2)
deep neural network
(2)
multi-task learning
(1)
catastrophic forgetting
(1)
unsupervised learning
(1)
transfer learning
(1)
graph laplacian
(1)
domain adaptation
(1)
information bottleneck
(1)
feature selection
(1)
feature correlation
(1)
active learning
(1)
granger causality
(1)
feature representation
(1)
neural network security
(1)
bregman divergence
(1)
time series generation
(1)
Papers
Start Smart: Leveraging Gradients For Enhancing Mask-based XAI Methods
ICLR 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
Aggregation of Dependent Expert Distributions in Multimodal Variational Autoencoders
ICML 2025
Jacobian Regularizer-based Neural Granger Causality
ICML 2024
Cauchy-Schwarz Divergence Information Bottleneck for Regression
ICLR 2024
Rethinking Information-theoretic Generalization: Loss Entropy Induced PAC Bounds
ICLR 2024
BAN: Detecting Backdoors Activated by Adversarial Neuron Noise
NIPS 2024
Domain Adaptation with Cauchy-Schwarz Divergence
UAI 2024
The Analysis of Deep Neural Networks by Information Theory: From Explainability to Generalization
AAAI 2023
Causal Recurrent Variational Autoencoder for Medical Time Series Generation
AAAI 2023
Robust and Fast Measure of Information via Low-Rank Representation
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