Jan Kieseler

[Gregor Kasieczka @GregorKasieczka]

Full paper at https://t.co/GID3ZWCUru.

Fun work with @DASHHPhD @quunihh student Sebastian and @JanKieseler & Mathias from @KITKarlsruhe

[Andy Buckley (@[email protected]) @agbuckley]

Nice to sneak this out just before Christmas: solid and actionable advice on designing and implementing LHC — and beyond — ML analysis strategies that can be re-used and combined, to deliver more impact (and citations...) https://t.co/UyYIo7NMi7

[Jan Kieseler @JanKieseler]

Are you looking for a postdoc in HEP and also want to push the boundaries of AI in a dynamic new group? Then check out this posting: https://t.co/0VnteN7ep0

[CERN Courier @CERNCourier]

Showcasing the first measurement, by @CMSexperiment, of the top-quark pair production cross section at a centre-of-mass energy of 13.6 TeV, TOP 2022 kicked off the #LHCRun3 top-quark physics programme
https://t.co/dJAfyESLbJ

[Jan Kieseler @JanKieseler]

@dorigo @Giles_C_Strong @MODECollaborat1 It’s a TeV-scale cosmic muon’s radiation in the camera I suppose ;)

[Jan Kieseler @JanKieseler]

First single-shot reconstruction of about 1000 particles at once in 200 PU in a high granularity calorimeter using machine learning, featuring GravNet and Object Condensation. Great work from @ShahRukhQasim and the whole team!
https://t.co/IUviktqb41

[Tommaso Dorigo @dorigo]

Congratulations to @JanKieseler, @pietrovischia, @Giles_C_Strong and others for the article "Intelligent Design for Particle Detectors", on the CERN EP Newsletter https://t.co/kM3aOGb5j6 @MODECollaborat1 #ArtificialIntelligence

[Jan Kieseler @JanKieseler]

@DrAndreDavid ARM? Amateurs. This is for pros: https://t.co/cUgxw1fP3A

[Jan Kieseler @JanKieseler]

@1cRebeca It’s like well aged wine, Rebeca

[Tommaso Dorigo @dorigo]

A first concrete proof of end to end optimization of experiments!! Forward with @MODECollaborat1 !!

[Jan Kieseler @JanKieseler]

@xmpierinix Was it in the top or bottom shelf?

[Jan Kieseler @JanKieseler]

@xmpierinix Yeah I’ll have the pleasure tomorrow. Trains in Germany are fun. But to make up for it you also don’t have mobile internet in many places!

[Pietro Vischia @pietrovischia]

Thrilled to announce that our white paper on End-to-End Optimization of Particle Physics Instruments with Differentiable Programming is finally out at https://t.co/xkZYK4wtjy !!!

[Amara Graps @amaragraps]

I think that this is the first time a physics demo had me laughing in tears.

[Tommaso Dorigo @dorigo]

Deep learning 66M parameters with a SGD-optimized nearest neighbor gets you to the same performance of NNs and BDTs! The power of ML is in differentiable calculus, as expected. https://t.co/BdvOOGB3tw

[Jan Kieseler @JanKieseler]

@1cRebeca I guess no. Too depressing ;)

[Jan Kieseler @JanKieseler]

Setting a trap for long lived and yet undiscovered particles
https://t.co/k3mZ7slIuh

[Juliette Alimena @AlimenaJuliette]

Les Houches Event ;)

[Jan Kieseler @JanKieseler]

https://t.co/WpC4ZMyka8
Will AI design our future detectors for us? One small step out of many steps towards AI helping us with design decisions is described in this paper, where we show how it can be used to easily compare different design options for measuring particle energies

[TensorFlow @TensorFlow]

🧪️ Engineers at the CERN LHC use TensorFlow to reconstruct thousands of particles in one go.

Learn how in this guest article by Jan Kieseler ↓ https://t.co/iXo6FFCOfU