Jeremias Knoblauch @LauchLab
Associate Professor & EPSRC Fellow @ UCL. Post-Bayesian seminar series sign-up @ https://t.co/a0MyAQOh16 Research mission @ https://t.co/kNIjvCrGne jeremiasknoblauch.github.io London Joined April 2019-
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𝗣𝗿𝗲𝗱𝗶𝗰𝘁𝗶𝘃𝗲𝗹𝘆 𝗢𝗿𝗶𝗲𝗻𝘁𝗲𝗱 𝗣𝗼𝘀𝘁𝗲𝗿𝗶𝗼𝗿𝘀 define a new statistical principle that derives model uncertainty from predictive accuracy. This predictively dominates classical approaches and avoids epistemic uncertainty from collapsing. arxiv.org/abs/2510.01915
I'm on the academic job market! I design and analyze probabilistic machine-learning methods---motivated by real-world scientific constraints, and developed in collaboration with scientists in biology, chemistry, and physics. A few highlights of my research areas are:
I am pleased to share our new NeurIPS paper for online Bayesian inference for neural networks. Instead of focusing on updating the parameter posterior, we work with the predictive posterior (which makes much more sense for non-identifiable models, and gives us more algorithmic freedom for developing faster methods).
Our paper “Martingale Posterior Neural Networks for Fast Sequential Decision Making” has been accepted at #neurips2025! Joint work with @l_sbetancourt, @AlvaroCartea and @sirbayes Blog: grdm.io/posts/bnn-with… Paper: arxiv.org/abs/2506.11898 Code: github.com/gerdm/martinga…
The application for a research fellowship at the Flatiron Institute in the Center for Computational Math is now live! This includes positions for ML and stats. The deadline is Dec 1. Links below with more details.
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-… @stats_UCL @uclcsml
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 @LauchLab @matialtamiranom
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!
New paper on Stationary MMD points 📣 arxiv.org/pdf/2505.20754 1️⃣ Samples generated by MMD flow exhibit 'super-convergence' 2️⃣ A discrete-time finite-particle convergence result for MMD flow Joint work with Toni Karvonen, Heishiro Kanagawa, @fx_briol, Chris J. Oates
🆕 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
Don't miss the very first workshop on post-Bayesian methods at UCL on May 15-16. Registration is now open!
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!
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…
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…
@tarantulae Thank you for the kind words!
Why posteriors MUST be modified, and a simple technic for setting them up. Dr. French's Modified Posteriors (1937) @ISBA_events abebooks.com/Dr-Frenchs-Mod…
Congratulations to @UCL / @stats_UCL's @matialtamiranom 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 @LauchLab and @fx_briol , as well as all my collaborators for their support!
Congratulations to @UCL / @stats_UCL's @matialtamiranom 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
@Chau9991 congrats! Looking forward to seeing your group grow :)
🥳🥳🥳Massive congratulations to my PhD student @matialtamiranom 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
@sirbayes thanks for the plug, Kevin! :)
📢 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!
Sam Power @sp_monte_carlo
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72K Followers 710 Following Research Scientist at Google DeepMind. Interested in Bayesian Machine Learning.
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