Jake @jakemrobertson.bsky.social and I are super excited to share that our paper “Do-PFN: In-Context Learning for Causal Effect Estimation” has been accepted at NeurIPS as a spotlight! Check out our pre-print on arXiv and stay tuned for the updated version: arxiv.org/abs/2506.06039 [1/7]

New preprint: SBI with foundation models! Tired of training or tuning your inference network, or waiting for your simulations to finish? Our method NPE-PF can help: It provides training-free simulation-based inference, achieving competitive performance with orders of magnitude fewer simulations! ⚡️

Can transformers learn full Bayesian inference in context? 🤔 👉 Come find out and visit our poster E-1205 in the East Hall this morning at #ICML2025 presented by @arikreuter.bsky.social icml.cc/virtual/2025...

Compute is increasing much faster than data. How can we improve classical supervised learning long term (the underlying tech of most of GenAI)? Our ICML position paper's answer: simply train on a bunch of artificial data (noise) and only do inference on real-world data! 1/n

We present a new approach to causal inference. Pre-trained on synthetic data, Do-PFN opens the door to a new domain: PFNs for causal inference—we are excited to announce our new paper “Do-PFN: In-Context Learning for Causal Effect Estimation” on Arxiv! 🔨🔍 A thread: 🧵[1/8]

It seems that we have 3 accepted papers at ICML 2025 🔥

Arriving in Singapore this afternoon 🛬 I'll attend #ICLR2025, #AABI2025, and #AISTATS2025 together with many of my students and collaborators to present our 2 orals, 5 posters, and 14 workshop contributions 🚀 Feel free to drop by!

BREAKING: People are being suspended on X in Turkey for posting videos of these protests against Erdoğan’s corrupt and repressive regime. Keep sharing everywhere.