Hanjing Wang
16 papers · 2022–2026 · 8 venues · across top CS/AI venues
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Achievements
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π Interdisciplinary Bridge Β· Silver πΊοΈ Taxonomy Completionist (34) π Conference Polyglot Β· Silver π€ Dynamic Duo (13) π Keyword Champion (2)
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Keyword Collector
(67)
π₯
Unstoppable Β· Bronze
β‘
Prolific Year Β· Productive
π
Renaissance Researcher
(6)
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Century Club Β· Bronze
Top co-authors
Research topics
Machine Learning
(11)
Optimization & Theory
(8)
Artificial Intelligence
(7)
Deep Learning
(6)
Bayesian & Probabilistic Β· Artificial Intelligence
(5)
Learning Types Β· Machine Learning
(5)
Core AI
(4)
Computer Vision
(3)
Analysis
(3)
Application Areas
(3)
Reinforcement Learning
(2)
Architectures
(2)
Bayesian & Probabilistic Β· Machine Learning
(2)
Core Methods
(2)
Learning Types Β· Deep Learning
(2)
Keywords
uncertainty quantification
(6)
epistemic uncertainty
(3)
variational inference
(2)
bayesian deep learning
(2)
out-of-distribution detection
(2)
gradient-based method
(2)
large language model
(2)
bayesian neural network
(2)
belief propagation
(2)
probabilistic inference
(2)
uncertainty attribution
(2)
bayesian inference
(2)
knowledge distillation
(1)
weakly supervised learning
(1)
domain generalization
(1)
reinforcement learning
(1)
map inference
(1)
self-attention mechanism
(1)
parallel computing
(1)
laplace approximation
(1)
Papers
CGU-Bayes: Causal Graph Uncertainty-Guided Bayesian Inference for Domain Generalization
CVPR 2026
Towards Knowledge-augmented Bayesian Deep Learning For Computer Vision
CVPR 2026
Boost, Disentangle, and Customize: A Robust System2-to-System1 Pipeline for Code Generation
ACL 2025
Bayesian Evidential Deep Learning for Online Action Detection
ECCV 2024
Beyond Dirichlet-based Models: When Bayesian Neural Networks Meet Evidential Deep Learning
UAI 2024
Epistemic Uncertainty Quantification For Pre-Trained Neural Networks
CVPR 2024
Integrating Markov Blanket Discovery into Causal Representation Learning for Domain Generalization
ECCV 2024
Optimization-based Uncertainty Attribution Via Learning Informative Perturbations
ECCV 2024
Theory-guided Message Passing Neural Network for Probabilistic Inference
AISTATS 2024
Body Knowledge and Uncertainty Modeling for Monocular 3D Human Body Reconstruction
ICCV 2023
Diversity-enhanced probabilistic ensemble for uncertainty estimation
UAI 2023
GEAR: A GPU-Centric Experience Replay System for Large Reinforcement Learning Models
ICML 2023
Gradient-Based Uncertainty Attribution for Explainable Bayesian Deep Learning
CVPR 2023
MALib: A Parallel Framework for Population-based Multi-agent Reinforcement Learning
JMLR 2023
Uncertainty-Guided Probabilistic Transformer for Complex Action Recognition
CVPR 2022
Variational message passing neural network for Maximum-A-Posteriori (MAP) inference
UAI 2022