Jonathan Stieber

@svpino Can I still join if I miss the first lecture?

Cohort 13 of the "Building Machine Learning Systems That Don't Suck" program starts tomorrow. There's no better place to learn how to build Machine Learning systems that work in the real world. It's a live class. It's tough. It's a ton of fun. ml.school

🎮 Check out the demo – train on three clients using the BCSS dataset! 📈 Integrated AIM support makes logging and visualizing results super easy. 🔜 Theoden is evolving! Stay tuned for regular updates as we continue to push the boundaries! 🚀👩‍🔬👨‍💻 #FederatedLearning

Tackling the intricate world of cross-silo federated learning in medical data 🩺💻, Theoden is your go-to research framework! ✨ Flexible: Easily incorporate new data, models, and methods without framework tweaks! 🛠️ Thank you @BMBF_Bund for the support.

🚀 Exciting news! Introducing #Theoden 🧠🌐 - The Open Distributed Learning Environment! 🏥🔬 With @NBabendererde, @mofuchs1, @anirbanakash #MECLabTUDA, @CS_TUDarmstadt 🐙github.com/MECLabTUDA/The…

𝙁𝙀𝘿-𝙋𝘼𝙏𝙃 Kick-off: a nation-wide🇩🇪 federated learning infrastructure for privacy-preserving computational #oncopathology. Joint effort across 4 pathology depts (@UKKoeln, @unimedhal, @UKL_Leipzig @UniklinikEssen) & @CS_TUDarmstadt, @Hessian_AI.🙏@BMBF_Bund for the support.

I am happy to announce that I have graduated with honors from the @TUDarmstadt with a Master's degree in Computer Science and am now starting my #PhD at #MECLabTUDA of @anirbanakash. I will be researching in the field of #digitalpathology and decentralized learning.

We have just started a large computational challenge: SemiCOL Challenge. semicol.org @ESDIPatho #DigitalPathology #ComputationalPathology @MICCAI_Society @TIAwarwick @jnkath @twittlabs @AI4Pathology @nmrajpoot @anirbanakash @DGPatho @ViktorKoelzer #ECDP2023

It is in great fear, not knowing what mighty artefact may appear, wield FrOoDo and evaluate artefacts in an easy and adaptable way.🔬🧫 So if you are in London at @The_CBIAS: Let's meet and chat. #MECLabTUDA #CBIAS2022 #microscopy 🧩github.com/MECLabTUDA/FrO…

Thank you @ElckeVels for writing such a balanced feature about our research on #Medical #AI @CS_TUDarmstadt & @Hessian_AI. A super team effort of many including @le_hekr, @kueglerd, @camgbus, @kalkjo, @mofuchs1, @JonStie, @amin_ranem et al.

Speak friend and clone the github repo for the latest feature update. To detect untrained creatures from a different age FrOoDo now supports classification and many more. @JonStie, @anirbanakash, @CS_TUDarmstadt #MECLabTUDA 🧩github.com/MECLabTUDA/FrO… 📄 arxiv.org/abs/2208.00963

It was great to see to much traffic for both our posters! 😁 Reach out if you have any further questions

Thank you to the Hoch3 team to cover our research on #surgical #ai in such a balanced fashion! A team effort from #MECLAbTUDA @CS_TUDarmstadt members: @le_hekr, @kueglerd, @mofuchs1, Johannes Fauser, @DhritimaanDas1 and many more.

🔥The shire is burning silently. So FrOoDo goes to MOOrDor.🔥 FrOoDo is a Framework for Out-of-Distribution Detection. We demonstrate its usefulness for computational pathology. With @JonStie, @y_tolkach & @anirbanakash #MECLabTUDA, @CS_TUDarmstadt 🧩github.com/MECLabTUDA/FrO…