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New Preprint Alert! 📢 Classical decision theory has helped humans make rational decisions under uncertainty for decades. Can it do the same for Large Language Models? We present DeLLMa (“dilemma”), a Decision-making LLM assistant. 🔗 DeLLMa.github.io 1/🧵

1/📯I am hiring!📯 Two-year postdoctoral position in Sample-Efficient Probabilistic Machine Learning Computer Science @ University of Helsinki with strong links to Finnish Center for AI 🦣 @[email protected] Please see blurb below, and full ad here: helsinki.fi/en/researchgro…

I am also hiring a PhD student to work on SBI with me and Samuel Kaski in connection with the grant. Position includes fully funded research visit to François-Xavier Briol's group UCL Statistical Science. aalto.wd3.myworkdayjobs.com/aalto/job/Otan…

Cost-aware Simulation-based Inference ift.tt/FkCDQz4

We present a simple and effective method to reduce the cost of simulations in SBI. The source code is available at github.com/huangdaolang/c…

1/ Excuse me, can I interest you in eliciting your beliefs as flexible probability distributions? No worries, we only need pairwise comparisons or rankings, no personal details. Led by **Petrus Mikkola** and joint with **Arto Klami**, to be presented soon at #NeurIPS2024

1/ Did they fool you into thinking that variational inference is just "the lesser way" of doing Bayesian inference? Please let me argue otherwise. lacerbi.github.io/blog/2024/vi-i… Or just come to play with the interactive VI widget that took me way too long to code up.

My collaborator Ayush Bharti will be presenting our recently accepted AISTATS paper on 'cost-aware simulation-based inference' at the next One World ABI Seminar on the 27th February. arXiv paper: arxiv.org/abs/2410.07930 Seminar series: warwick.ac.uk/fac/sci/statis…

1/ Introducing ACE (Amortized Conditioning Engine)! Our new paper AISTATS Conference presents a transformer framework that unifies tasks from image completion to BayesOpt & simulator-based inference under *one* probabilistic conditioning approach. It's Bayes all the way down!

1/ We asked GPT-4.5 -- allegedly the model with the best sense of humor, according to you folks -- to write a comic about our recent AISTATS paper on the Amortized Conditioning Engine (ACE). Then gpt-4o drew it. You judge the result... (thread continues 👇)

New blog post! You can train a neural network to *just do things* -- such as *predict the optimum of a function*. But how do you get a big training dataset of "functions with known optima"? Read the blog post to find out! (link 👇)