
Siu Lun Chau
@chau9991
Incoming Assistant Professor of Statistical Machine Learning @ CCDS, NTU Singapore. Previously postdoc@CISPA, DPhil@oxcsml, Interned@AmazonUK and @MPI_IS.
ID: 1280508003452665860
https://chau999.github.io 07-07-2020 14:24:41
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🎉Thrilled to share that our paper “Truthful Elicitation of Imprecise Forecasts” has been accepted as an Oral presentation at #UAI2025! 🙌 Check it out: arxiv.org/pdf/2503.16395 Anurag Singh@ UAI Krikamol (Hiring Postdoc)

Happy to share I've been nominated Action Editor of Accepted papers at TMLR. If you have papers on • Imprecise Probabilistic Machine Learning, • Aleatoric vs Epistemic Uncertainty Quantification and Representation, • Conformal Prediction, • Evidential Learning, submit to TMLR! 😀



🚨 Ever wonder why we have kernel mean embeddings but not kernel *quantile* embeddings? What do we gain (a lot) or lose (not much) if so? Wait, what even are quantiles in RKHS? 🤯 Curious? 👉 rb.gy/6ilcbp Joint work with Masha Naslidnyk, François-Xavier Briol , Krikamol (Hiring Postdoc)!


In the presence of noisy data, the learner faces epistemic uncertainty (EU) at test time which, in many cases, cannot be resolved on the basis of training data alone. What to do then? Sabina Sloman, Samuel Kaski and I tried to answer this in arxiv.org/abs/2505.23496 1/3







