📢 Check out this new work on robustness coming out of our xAI Lab at the Universität Bamberg. Work lead by Sebastian Doerrich (congrats!) who will present details in Vancouver at #MICCAI23 MLMI. Sounds exciting? We also have an open PhD/PostDoc position: uni-bamberg.de/en/ai/chair-of…

#NewDawn Applications still possible. Join our xAILab as PhD or PostDoc and become part of the newly founded Bamberg Center of Artificial Intelligence (BaCAI). Details below. #hightechagendabayern #ResearchBavaria #ResearchGermany

📄Paper towards more interpretable and privacy-aware classifiers accepted at #ISBI2024. Details👇 Very proud of this amazing team effort by Sebastian Doerrich Tobias Archut Francesco. Congrats!!🎆 🎓Interested in research projects within our group? Details uni-bamberg.de/en/ai/chair-of…

Congrats on this recognition of an exceptional research project and thesis by DMEA - Connecting Digital Health 2024. Work at our xAILab Bamberg. We’re also hiring: uni-bamberg.de/en/ai/chair-of…

Big shoutout to Tobias for securing third place at the DMEA - Connecting Digital Health Newcomer Award!🥉 Please join us at the xAI Lab Bamberg in celebrating this remarkable achievement!👏 Learn more: uni-bamberg.de/en/xai/news/ar… Explore our research at xAI Lab Bamberg: uni-bamberg.de/en/ai/chair-of… Fakultät WIAI - Uni Bamberg

📣 Comparison of performance of backbones (AlexNet to Found. Model) and classification paradigms (kNN to end2end) on 12 medical datasets. -> comprehensive baseline on MedMNIST+ -> informs baseline choise and the influence of input resolution Paper: arxiv.org/abs/2404.15786

Integrating kNN with foundation models has many benefits including improved data efficiency and ability to address privacy constraints. Sebastian Doerrich currently presenting at #isbi2024. Stop by at poster #980. 📄 arxiv.org/abs/2402.12500 #hightechagenda

Amazing social event at #isbi2024. Run in the Panathenaic Stadium. #stayactive

Another One!📢 Excited to share that our paper "Self-supervised Vision Transformer are Scalable Generative Models for Domain Generalization" is accepted at #MICCAI2024! Want to know more? 📝: arxiv.org/abs/2407.02900 🐙: github.com/sdoerrich97/vi… MICCAI @xAILabBamberg

📣 I am happy to share that our paper "MedMNIST-C: Comprehensive benchmark and improved classifier robustness by simulating realistic image corruptions" has been accepted to the #ADSMI workshop at #MICCAI2024! MICCAI ADSMI Workshop @ MICCAI2024 Paper: arxiv.org/pdf/2406.17536