Frank Hutter
@FrankRHutter
Founder of @Prior_Labs, Prof of #machinelearning at ELLIS Institute Tübingen & Uni Freiburg, 3x ERC Grant holder, EurAI & ELLIS fellow. All opinions are my own.
The data science revolution is getting closer. TabPFN v2 is published in Nature: nature.com/articles/s4158… On tabular classification with up to 10k data points & 500 features, in 2.8s TabPFN on average outperforms all other methods, even when tuning them for up to 4 hours🧵1/19
Join our mission to strengthen AI research in Europe 🇪🇺 We are looking for several ML Research Engineers and Scientists to work on OpenEuroLLM at the ELLIS Institute Tübingen. If you're passionate about large-scale model training, multilingual evaluation and want to contribute to…
We’re excited to welcome exceptional talent from the #ELLIS network and beyond to @prior_labs! We’re building a diverse world-class team and warmly welcome applications from women and underrepresented groups in tech. Please share with your network 😊
🏹 Job alert: ML Engineer at @prior_labs 📍Freiburg or Berlin 🇩🇪 📅 Apply by Dec 31 🔗 More info: jobs.ashbyhq.com/prior-labs/a1d… Prior Labs is a VC-backed deep tech startup that grew out of the ELLIS ecosystem, with @FrankRHutter and @bschoelkopf among the co-founders.
It's great to have this new open-source benchmark for tabular data 🚀 It's really comprehensive, created and maintained by serious open source contributors from various groups, and I expect it to quickly become the new standard benchmark. I'm super excited that progress in the…
🚨What is SOTA on tabular data, really? We are excited to announce 𝗧𝗮𝗯𝗔𝗿𝗲𝗻𝗮, a living benchmark for machine learning on IID tabular data with: 📊 an online leaderboard (submit!) 📑 carefully curated datasets 📈 strong tree-based, deep learning, and foundation models 🧵
Something new is coming at @prior_labs: reasoning meets tabular data. We can now improve predictions over the strong statistical reasoning of TabPFN v2 by contextual reasoning about real-world knowledge. Soft-launching soon in our Discord -- join here for early access:…
Super excited about this interventional version of TabPFN! We rarely make predictions just for the sake of making predictions, but rather in order to make (automated) decisions. If these decisions entail interventions on some of the features (treatments, prices, purchases, etc),…
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:
Excited to speak at @PyConDE today, presenting TabPFN v2, including a live demo. 10:55am, in person in Platinum 3. If you're at the conference please find me to chat about tabular foundation models and @prior_labs 🙂
I'm truly excited to share our vision at @prior_labs, going far beyond TabPFN. Our vision is bold: creating truly agentic AI systems capable of understanding high-level goals, fusing tables, language, and images with domain knowledge, to reason, infer causality, and adapt…
📢 We are excited to announce "#FMSD: 1st Workshop on Foundation Models for Structured Data" has been accepted to #ICML 2025! Call for Papers: icml-structured-fm-workshop.github.io/call-for-paper…