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Thomas Fischer, Eike Middell, Shakiba Moradi and Alexander von Lühmann
fNIRS Single-trial decoding improves systematically with higher optode density, model-based noise regression, and image reconstruction
Barrie Kersbergen, Olivier Sprangers, Bojan Karlas, Maarten de Rijke, Sebastian Schelter
Illoominate – Data Shapley Values for Debugging Neighborhood-based Recommender Systems
Gereon Dusella, Haralampos Gavriilidis, Volker Markl, Eleni Tzirita Zacharatou
Benchmarking Spatial Operations over Heterogeneous Data: The Case of Zonal Statistics
Yanqing Luo, Julius Hense, Niklas Prenißl, Andreas Mock, Klaus-Robert Müller, Thomas Schnake, Mina Jamshidi Idaji
Symb-xMIL: Symbolic Explanations for Multiple Instance Learning in Digital Pathology
Marco Morik, Xiao Ruiting, Shinichi Nakajima, Stefan Haufe, Ismail Huseynov
Structure-Preserving Correction Learning for Sparse Bayesian Inference in Brain Source Imaging
Anja Hirsch, Foo Wei Ten, Kyle S. Krüger, Robin C. Geyer, Tobias Röschl, Matthias I Gröschel, Paul Rostin, Roland Eils, Martin Spott, Fabian Prasser et al.
The Multimodal Anonymizer: a fully local multi-agent AI system for medical data deidentification
Leo Benning, Anja Hirsch, Matthias Gröschel, Tobias Röschl, Martin Spott, Felix Patricius Hans, Tim Urban, Hans-Jörg Busch, Alexander Meyer, Julian Madrid et al.
Performance evaluation and benchmarking across 16 large language models on a comprehensive real-world emergency department triage data set
Yilong Wang, Qianli Wang, Bohao Chu, Yihong Liu, Jing Yang, Simon Ostermann
Enhancing Multilingual Counterfactual Generation through Alignment-as-Preference Optimization
Alexander Möllers, Marvin Sextro, Julius Hense, Gabriel Dernbach, Klaus-Robert Müller
In-Context Multiple Instance Learning
F. Ratajczak, F. Hohendanner, S. Haack, L. Boldt, A. S. Parwani, F. Blaschke, M. Schneider-Reigbert, F. Spinka, M. Bock, A. Meyer et al.