Published

ICML
14. Domain Generalisation via Imprecise Learning
Anurag Singh, Siu Lun Chau, Shahine Bouabid, Krikamol Muandet
International Conference on Machine Learning (ICML), 2024
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AAAI
13. Causal Strategic Learning with Competitive Selection
Kiet QH Vo, Muneeb Aadil, Siu Lun Chau, Krikamol Muandet
(Oral) The 38th Annual AAAI Conference on Artificial Intelligence, 2024
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AISTATS
12. Looping in the Human: Collaborative and Explainable Bayesian Optimization
Masaki Adachi, Brady Planden, David A. Howey, Krikamol Maundet, Michael A. Osborne, Siu Lun Chau
The International Conference on Artificial Intelligence and Statistics (AISTATS), 2024
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Ph.D. Thesis
11. Towards Trustworthy Machine Learning with Kernels
Siu Lun Chau
Ph.D. Thesis, 2023
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NeurIPS
10. Explaining the Uncertain: Stochastic Shapley Values for Gaussian Process Models
Siu Lun Chau, Krikamol Muandet*, Dino Sejdinovic*
(Spotlight) Conference on Neural Information Processing Systems (NeurIPS), 2023
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TMLR
9. Gated Domain Units for Multi-source Domain Generalization
Simon Föll*, Alina Dubatovka*, Eugen Ernst†, Siu Lun Chau†, Martin Maritsch, Patrik Okanovic, Gudrun Thäter, Joachim M Buhmann, Felix Wortmann,Krikamol Muandet
Transactions on Machine Learning Research, 2023
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ECML
8. Spectral ranking with covariates
Siu Lun Chau, Mihai Cucuringu, Dino Sejdinovic
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), 2022
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NeurIPS
7. RKHS-SHAP: Shapley Values for Kernel Methods
Siu Lun Chau, Robert Hu, Javier Gonzalez, Dino Sejdinovic
Conference on Neural Information Processing Systems (NeurIPS), 2022
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NeurIPS
6. Explaining Preferences with Shapley Values
Hu Robert*, Siu Lun Chau*, Jaime Ferrando Huertas, Dino Sejdinovic
Conference on Neural Information Processing Systems (NeurIPS), 2022
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AISTATS
5. Learning Inconsistent Preferences with Gaussian Processes
Siu Lun Chau, Javier González, Dino Sejdinovic
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
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NeruIPS
4. Giga-scale Kernel Matrix Vector Multiplication on GPU
Robert Hu, Siu Lun Chau, Dino Sejdinovic, Joan Alexis Glaunès
Conference on Neural Information Processing Systems (NeurIPS), 2022
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IEEE
3. Kernel-based graph learning from smooth signals: A functional viewpoint
Xingyue Pu, Siu Lun Chau, Xiaowen Dong, Dino Sejdinovic
IEEE Transactions on Signal and Information Processing over Networks, 2021
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NeurIPS
2. Deconditional Downscaling with Gaussian Processes
Siu Lun Chau*, Shahine Bouabid*, Dino Sejdinovic
Conference on Neural Information Processing Systems (NeurIPS), 2021
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NeurIPS
1. BayesIMP: Uncertainty Quantification for Causal Data Fusion
Siu Lun Chau*, Jean-François Ton*, Javier González, Yee Whye Teh, Dino Sejdinovic
Conference on Neural Information Processing Systems (NeurIPS), 2021
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