Siu Lun Chau
Assistant Professor
Develops uncertainty-aware machine learning using imprecise probabilities, kernel methods and cooperative game theory.
Siu Lun Chau's lab at NTU works on learning theory & optimization, probabilistic & causal inference and data management & big data. 23 papers since 2023, 20 at top venues, mostly UAI and ICML.
At a glance
- papers, 2023–2026
- 6/ year
- at T1 venues
- 87%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom the lab homepage, 2023–2026
- 12 papers2026 · T1 10 · collecting
- 6 papers2025 · T1 5
- 3 papers2024 · T1 3
- 2 papers2023 · T1 2
T1 venuesOtherVenues: UAI, ICML, AISTATS, NeurIPS, AAAI
Research focuspaper titles that use each topic's words
- Learning theory & optimization5 papers
- Probabilistic & causal inference4 papers
- kernel2 papers
- kernel methods1 paper
- Data management & big data0 papers
Paper list
From the lab homepage.
202612 papers
- NeurIPS (T1)Amortized Linear-time Exact Shapley Value for Product-Kernel Methods
- AI4ScienceDynamic Large Language Model Representations for Multi-Objective Chemical Reaction Optimisation
- AAAI (T1)Exact shapley attributions in quadratic-time for fanova gaussian processes
- AISTATS (T1)Explanation Design in Strategic Learning: Sufficient Explanations that Induce Non-harmful Responses
- EIMLHow do Consonance Constructions Shape Conformal Credal Sets?
- UAI (T1)Instrumental and Proximal Causal Inference with Gaussian Processes
- ICML (T1)Learning Credal Ensembles via Distributionally Robust Optimization
- ICML (T1)Off-Policy Evaluation with Strategic Agents via Local Disclosure
- UAI (T1)Quantification of Credal Uncertainty: A Distance-Based Approach
- UAI (T1)Robust Predictive Uncertainty and Double Descent in Contaminated Bayesian Random Features
- UAI (T1)Set-based vs Distribution-based Representations of Epistemic Uncertainty: A Comparative Study
- UAI (T1)Verbalizing LLM's Higher-order Uncertainty via Imprecise Probabilities
20256 papers
- AISTATS (T1)Credal Two-Sample Tests of Epistemic Uncertainty
- Nature Communications (T1)Highly parallel optimisation of chemical reactions through automation and machine intelligence
- EurIPS PAIG WorkshopIncentive Aware AI Regulation
- NeurIPS (T1)Integral Imprecise Probability Metrics
- ICML (T1)Kernel Quantile Embeddings and Associated Probability Metrics
- UAI (T1)Truthful Elicitation of Imprecise Forecasts
20243 papers
- AAAI (T1)Causal strategic learning with competitive selection
- ICML (T1)Domain generalisation via imprecise learning
- AISTATS (T1)Looping in the Human: Collaborative and Explainable Bayesian Optimization
20232 papers
- NeurIPS (T1)Explaining the uncertain: Stochastic shapley values for gaussian process models
- TMLR (T1)Gated Domain Units for Multi-source Domain Generalization
Where alumni went
Alumni are not listed on the lab homepage.
Apply to NTUFall 2027
Not announced yet
Computing and Data Science PhD
- Round
- Main
- Opens
- —
- GRE
- not required
- English
- TOEFL/IELTS
- Fee
- See program page
Not yet confirmed for this intake.
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- USGeorgia Tech
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Data
Some numbers could not be verified:
- The member list could not be found on the lab site.
- The alumni list could not be found on the lab site.
- Collected
- Verified
- Papers
- The lab homepage
- Members
- Not collected
- Alumni
- Not collected
Tiers are venue classifications, not lab rankings.