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Showing papers from Charité - Universitätsmedizin Berlin Show all papers

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NeurIPS 2026StanfordUniversity College London, UniveImperial College LondonCharité - Universitätsmedizin BeU CambridgeBiosignals & wearables

OpenMHC: Accelerating the Science of Wearable Foundation Models

OpenMHC releases the largest open wearable health dataset with open-source foundation models and a unified benchmark across prediction, imputation, and forecasting tasks.

Narayan Schütz, Yuze Bai, Lianggang Pan, Edgar Eggert and 15 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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lenient 5/5
medium 5/10
strict 2/5
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NeurIPS 2026TU Berlin/BIFOLDTU Berlin, BIFOLDCharité - Universitätsmedizin BeLudwig-Maximilians-Universität MTU BerlinExplainable AI

Symb-xMIL: Symbolic Explanations for Multiple Instance Learning in Digital Pathology

Symb-xMIL quantifies alignment between MIL predictions and human-readable logical rules to expose decision patterns, recover ground-truth rules, and refine survival stratification beyond HPV status.

Yanqng Luo, Julius Hense, Niklas Prenißl, Andreas Mock and 3 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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lenient 5/5
medium 7/10
strict 0/5
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NeurIPS 2026Robert Koch Institute/Charite MeCharité - Universitätsmedizin BeRobert Koch InstituteRepresentation & contrastive learning

Conveyance: A Versatile Framework for Learning in Structured Class Spaces

Conveyance proposes a structured loss maximizing margins over class partitions to exploit class relations, matching or exceeding specialized baselines in hierarchical, ordinal, and multiple-instance tasks.

Yasser Taha, Grégoire Montavon, Nils Körber

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026

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AI panel: 7 of 20 reviewers recommend it
lenient 3/5
medium 4/10
strict 0/5