Excited to share: “A Tale of Two Classes: Adapting Supervised Contrastive Learning to Binary Imbalanced Datasets” has been accepted to #CVPR2025! 🎉
Paper: lnkd.in/esKRqF5p
Code: lnkd.in/eZFvDA5Q
(Thread incoming 👇)
01.04.2025 13:37 — 👍 12 🔁 5 💬 1 📌 0
That clinician really shouldn't be wearing a watch close to the MR scanner...
01.04.2025 09:39 — 👍 1 🔁 0 💬 1 📌 0
signal processing+ML researcher | EEG+brain dynamics | PhD from @UGent
PI at Helmholtz AI, Faculty at TU Munich, Fellow at Zuse School for reliable AI, Branco Weiss Fellow, ELLIS Scholar.
Prev: Cambridge CBL, St John's College, ETH Zürich, Google Brain, Microsoft Research, Disney Research.
https://fortuin.github.io/
www.neeldey.com
Faculty member at Harvard Med/MGH. Likes: biomedical computer vision, representation learning
Previous: Postdoc at MIT CSAIL, PhD from NYU CS
Manchester Centre for AI FUNdamentals | UoM | Alumn UCL, DeepMind, U Alberta, PUCP | Deep Thinker | Posts/reposts might be non-deep | Carpe espresso ☕
Chair of AI in Healthcare and Medicine, led by @danielrueckert.bsky.social, at TU Munich.
🌐 www.kiinformatik.mri.tum.de/en/chair-artificial-intelligence-healthcare-and-medicine
PhD candidate in Medical Imaging @ AI Mecine TUM with Daniel Rueckert
Professor for Human-Centred Transformative AI @ Hasso-Plattner-Institut. Previously @ Google DeepMind, Imperial College London, TU Munich. 🇪🇺 🏳️🌈
https://www.g-k.ai
Postdoc at AIDE Lab @stanfordmedicine.bsky.social | prev. MEC Lab @cs-tudarmstadt.bsky.social | Continual Learning and Monitoring for Medical Image Computing
Senior Lecturer and Researcher @LMU_Muenchen working on #ExplainableAI / #interpretableML and #OpenML
physician-scientist, author, editor
https://www.scripps.edu/faculty/topol/
Ground Truths https://erictopol.substack.com
SUPER AGERS https://www.simonandschuster.com/books/Super-Agers/Eric-Topol/9781668067666
Teaching computers chemistry. Helping data sets with people problems. Sailing the sea. Opinions my own.
Bühne frei für die Wissenschaft! Forscher*innen präsentieren ihre Arbeit in kurzen und mitreißenden Vorträgen.
Website: https://www.scienceslam.de/
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Working at microsoft research health futures. Interested in causal representation learning and generative modelling applied to medical data.
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PhD student interested in benchmarking medical LLMs and understanding how to best use tabular data in deep learning.
Die DFG ist die größte Forschungsförderorganisation und die Selbstverwaltungsorganisation der Wissenschaft in Deutschland.
www.dfg.de
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PhD Candidate @ AI in Medicine Lab at Technical University of Munich
