Siu Lun Chau
19 papers · 2021–2026 · 5 venues · across top CS/AI venues
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Artificial Intelligence
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Core AI
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Bayesian & Probabilistic · Artificial Intelligence
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Bayesian & Probabilistic · Machine Learning
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Optimization & Theory · Machine Learning
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Keywords
gaussian process
(5)
epistemic uncertainty
(5)
shapley value
(4)
credal set
(4)
bayesian inference
(3)
uncertainty quantification
(3)
kernel methods
(3)
model interpretability
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feature attribution
(2)
explainable ai
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kernel mean embedding
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preference learning
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reproducing kernel hilbert space
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causal inference
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sliced wasserstein distance
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probability metrics
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kernel matrix
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in-context learning
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game theory
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numerical approximation
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Papers
Exact Shapley Attributions in Quadratic-time for FANOVA Gaussian Processes
AAAI 2026
Instrumental and Proximal Causal Inference with Gaussian Processes
UAI 2026
Quantification of Credal Uncertainty: A Distance-Based Approach
UAI 2026
Robust Predictive Uncertainty and Double Descent in Contaminated Bayesian Random Features
UAI 2026
Set-based v.s. Distribution-based Representations of Epistemic Uncertainty: A Comparative Study
UAI 2026
Verbalizing LLM’s Higher-order Uncertainty via Imprecise Probabilities
UAI 2026
Credal Two-Sample Tests of Epistemic Uncertainty
AISTATS 2025
Kernel Quantile Embeddings and Associated Probability Metrics
ICML 2025
Truthful Elicitation of Imprecise Forecasts
UAI 2025
Causal Strategic Learning with Competitive Selection
AAAI 2024
Domain Generalisation via Imprecise Learning
ICML 2024
Looping in the Human: Collaborative and Explainable Bayesian Optimization
AISTATS 2024
Explaining the Uncertain: Stochastic Shapley Values for Gaussian Process Models
NeurIPS 2023
Explaining Preferences with Shapley Values
NeurIPS 2022
Giga-scale Kernel Matrix-Vector Multiplication on GPU
NeurIPS 2022
Learning Inconsistent Preferences with Gaussian Processes
AISTATS 2022
RKHS-SHAP: Shapley Values for Kernel Methods
NeurIPS 2022
BayesIMP: Uncertainty Quantification for Causal Data Fusion
NeurIPS 2021
Deconditional Downscaling with Gaussian Processes
NeurIPS 2021