Michael Krämer

Three-year postdoctoral fellowship opening at the MCMP; please help us spread the word.

»Protonen haben keine Rechte« | vor:denker Wenn die Teilchenphysiker in der Nähe von Genf 40 Millionen Kollisionen pro Sekunde erzeugen, sind sich Physik und Künstliche Intelligenz ganz nah. Dann generiert der Teilchenbeschleuniger des Europäi...

Interview (in German) I recently gave to the FAZ Vor:Denker on AI, Physics, and how they do & will benefit each other.

vordenker.faz.net/protonen-hab...

Large Physics Models: Towards a collaborative approach with Large Language Models and Foundation Models This paper explores ideas and provides a potential roadmap for the development and evaluation of physics-specific large-scale AI models, which we call Large Physics Models (LPMs). These models, based ...

With @henkderegt.bsky.social, @danielkostic.bsky.social, @kasieczka.bsky.social and others, we have submitted a white paper that provides a potential roadmap for the development and evaluation of physics-specific AI models: arxiv.org/abs/2501.05382, see also www.lorentzcenter.nl/physics-en-q....

We also provide the AspenOpenJets dataset for further public use in ML applications: www.fdr.uni-hamburg.de/record/16505

Aspen Open Jets: Unlocking LHC Data for Foundation Models in Particle Physics Foundation models are deep learning models pre-trained on large amounts of data which are capable of generalizing to multiple datasets and/or downstream tasks. This work demonstrates how data collecte...

Foundation models play an increasingly important role in physics. With @ozamram.bsky.social @joschkabirk.bsky.social @kasieczka.bsky.social et al. we have trained a FM on 180M particle physics events from the LHC and shown the performance in generating synthetic data: arxiv.org/abs/2412.10504.

🚨 FINAL REMINDER 🚨: Multiple Postdoc and PhD positions in our AI + Physics cluster in DAMTP, Cambridge!

Deadlines:
- Postdoc: Jan 5th (Sunday)
- PhD: Jan 7th (Tuesday)

More info below – Please share with researchers and students who might be interested in joining us!

INSPIRE and social media: Update your INSPIRE profile to add your accounts to your profile and keep in touch with us.

blog.inspirehep.net/2024/12/insp...

Madrid gets ready for the New Year... ¡Feliz año nuevo!

We prepared 180M jets from 2016 CMS data taking to be easily used for machine learning & demonstrate their use for pre-training.

Data at: www.fdr.uni-hamburg.de/record/16505
Paper at: arxiv.org/abs/2412.10504

w/ @ozamram.bsky.social, @joschkabirk.bsky.social, @mikraemer.bsky.social & others