🔥The 9th Round of Easy Loan, Earn $40 Reward is in progress❗️ ⏰ Promotion Period: January 15th - Feburary 15th, 2025 👉 Register now and check more details at gate.io/campaigns/358

🙌🎉Our 2025 recipient of the COPSS Presidents' Award, is Lester Mackey! This award is given annually to a young member of the statistical community in recognition of outstanding contributions to the profession of statistics.

Interested in learning about Kernel Discrepancies❓ Maximum Mean Discrepancy Hilbert-Schmidt Independence Criterion Kernel Stein Discrepancy 🧐 Don't know where to begin? 👀 Check out my Practical Introduction to Kernel Discrepancies: MMD, HSIC & KSD! arxiv.org/abs/2503.04820

An excellent overview of recent results on kernel discrepancies!

The last table you need on kernel hypothesis testing!

Farewell Party for Siu Lun Chau who has been with our lab for over two years as a postdoc. He will soon start his lab as an Assistant Professor NTU Singapore This mark the end of his time with us, but will start a lifelong collaboration. We wish him success in his adademic endevour.

Check out our two-sample credal testing paper for settings in which even the existence of the two distributions to test is not guaranteed! 🤯🧐 #AISTATS2025

Density Ratio-based Proxy Causal Learning Without Density Ratios 🤔 at #AISTATS2025 An alternative bridge function for proxy causal learning with hidden confounders. arxiv.org/abs/2503.08371 Bariscan Bozkurt, Ben Deaner, Dimitri Meunier LY9988

Spectral Representation for Causal Estimation with Hidden Confounders at #AISTATS2025 A spectral method for causal effect estimation with hidden confounders, for IV and proxy causal learning arxiv.org/abs/2407.10448 Haotian Sun Antoine Moulin Tongzheng Ren Bo Dai

📢 We have an opportunity for students to join our PhD programme in Theoretical Neuroscience and Machine Learning this September. Application deadline is 27 May 2025. Information & how to apply 👉 ucl.ac.uk/gatsby/study-a…

Credal Two-Sample Tests of Epistemic Uncertainty at #AISTATS25 Compare credal sets: convex sets of prob measures where elements capture aleatoric uncertainty and set itself represents epistemic uncertainty. arxiv.org/abs/2410.12921 Siu Lun Chau Antonin Schrab Dino Sejdinovic Krikamol (Hiring Postdoc)

Kernel Single Proxy Control for Deterministic Confounding at #AISTATS2025 Proxy causal learning generally requires two proxy variables - a treatment and an outcome proxy. When is it possible to use just one? arxiv.org/abs/2308.04585 LY9988

Oral #AISTATS25 Robust Kernel Hypothesis Testing under Data Corruption -Robustify any permutation test to be immune to data corruption of up to X samples -MMD HSIC robust minimax optimality Monday 5 May -Oral Session 7 Robust Learning -Poster Session 3 Presented by Ilmun Kim

At 3:30pm UK time, my PhD student Masha will be speaking about kernel quantiles (and associated distances) at the Isaac Newton inst. Tune in at m.youtube.com/watch?v=p-rZuo… to learn how to use quantiles in RKHS to efficiently represent/compare distributions on general spaces.

Cursor is now free for students. Enjoy!

🚨 New paper accepted at SIMODS! 🚨 “Nonlinear Meta-learning Can Guarantee Faster Rates” arxiv.org/abs/2307.10870 When does meta learning work? Spoiler: generalise to new tasks by overfitting on your training tasks! Here is why: 🧵👇

We've written a monograph on Gaussian processes and reproducing kernel methods. arxiv.org/abs/2506.17366

🎊 Congratulations to Kevin Huang (Kevin Han Huang) on passing his PhD viva with minor corrections! 🥳 🔖 Universality beyond the classical asymptotic regime

Distributional diffusion models with scoring rules at #icml25 Fewer, larger denoising steps using distributional losses! Wednesday 11am poster E-1910 arxiv.org/pdf/2502.02483 Alexandre Galashov Valentin De Bortoli Guntupalli Guangyao (Stannis) Zhou Kevin Patrick Murphy Arnaud Doucet