Happy to share that our paper "Robust and Conjugate Gaussian Process Regression" has been accepted as a spotlight at #ICML2024. We proposed a robust Gaussian process regression at virtually no added cost! Joint work with François-Xavier Briol and Jeremias Knoblauch, all research UCL Statistical Science. [1/6]

We have a faculty position coming up; get in touch/PM me if you'd like to join us at UCL! Deadline 28th of August. Compensation substantially higher than listed (can give details per PM)

Matias Altamirano Montero will present two papers at ICML Conference on how generalised Bayes can make probabilistic ML robust and scalable. Say hi to him! Spotlight paper on GPs -Wed HallC 4-9 #1506: arxiv.org/abs/2311.00463 Paper on KF -Tues HallC 4-9 #1602: arxiv.org/abs/2405.05646 Jeremias Knoblauch

Applications are invited for 1 PhD Studentship (UK fee only) based at the Department of Statistical Science, University College London. The position can involve any topic within the Statistical Science remit. Deadline for applications: 16 August 2024 ucl.ac.uk/statistics/pro…

Friends, I'm excited to share some professional news: - I'll be promoted to Associate Professor in October - my research won the Savage Award (tinyurl.com/pvm6vpfk) - I've started working at the nexus of ML & consumer/human rights with FoxGlove (NGO) and Leigh Day (law firm)

Interested in reducing the computational cost of running simulations in simulation-based inference (SBI)? Check out our new “Cost-aware SBI” paper w. Daolang Huang Samuel Kaski François-Xavier Briol arxiv.org/abs/2410.07930 Thread👇

📢 Post-Bayesian online seminar series coming!📢 To stay posted, sign up at tinyurl.com/postBayes We'll discuss cutting-edge methods for posteriors that no longer rely on Bayes Theorem. (e.g., PAC-Bayes, generalised Bayes, Martingale posteriors, ...) Pls circulate widely!

🥳🥳🥳Massive congratulations to my PhD student Matias Altamirano Montero for winning one of the 3 Bloomberg Fellowships for his work on robust & efficient post-Bayesian methods! I cannot think of anyone more deserving!😊 Read more at tinyurl.com/MatiasBloomberg

Congratulations to @UCL / UCL Statistical Science's Matias Altamirano Montero on being one of the 2024-2025 Bloomberg #DataScience Ph.D. Fellows! Learn more about Matías’ research focus and our latest cohort of Ph.D. Fellows: bloom.bg/4itDDiN #AI #ML #NLProc #NeurIPS2024

Super happy and grateful to be awarded the Bloomberg fellowship. Huge thanks to my amazing supervisors Jeremias Knoblauch and François-Xavier Briol , as well as all my collaborators for their support!

Why posteriors MUST be modified, and a simple technic for setting them up. Dr. French's Modified Posteriors (1937) ISBA abebooks.com/Dr-Frenchs-Mod…

We are excited to announce that registration for the inaugural post-Bayes workshop on May 15./16. at UCL is now open! Website: postbayes.github.io/workshop2025/ Registration link: tinyurl.com/postBayesWorks…

Looking forward to speaking at the Post-Bayes workshop in May!

Don't miss the very first workshop on post-Bayesian methods at UCL on May 15-16. Registration is now open!

🆕 The ELLIS Unit London (UCL) will host the first workshop uniting disparate subfields of post-Bayesian methods, including PAC Bayes, generalized Bayes, predictive resampling, Martingale posteriors, and online learning. 📍 London 🏴󠁧󠁢󠁥󠁮󠁧󠁿 📅 May 15-16 🔗 bit.ly/3GgwZ0G

There’s been lots of interest in gradient flows, but I’ve been a bit sceptical as I wasn’t clear on the advantages. This paper shows that MMD gradient flows can integrate a large class of functions exactly without needing to converge to a global minimum: stationarity is enough!

Videos from the recent UCL workshop on ‘Advances in Post-Bayesian methods’ are now available on YouTube! Check these out if you couldn’t make it: tinyurl.com/AdvPostBayes Jeremias Knoblauch Matias Altamirano Montero

Today is the day of the pre-ICML event at UCL! Come check out the exciting work from academics, industry researchers, postdocs and PhD students from around London: sites.google.com/view/pre-icml-… UCL Statistical Science UCL CSML