1.3k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Ludwig-Maximilians-Universität MünchenDE63 papers
- Technical University of MunichDE41 papers
- LMU KlinikumDE29 papers
- Imperial College LondonGB8 papers
- Helmholtz MunichDE6 papers
- TUM KlinikumDE6 papers
- Zimmer Biomet (Germany)DE6 papers
- Fraunhofer Institute for Integrated CircuitsDE4 papers
- Munich School of PhilosophyDE4 papers
- TU Dortmund UniversityDE4 papers
- University College LondonGB4 papers
- Zimmer Biomet (Netherlands)NL4 papers
18 papers · 1 filter
Distribution Matching for Graph Quantification Under Structural Covariate Shift
Clemens Damke, Eyke Hüllermeier
Graphs are commonly used in machine learning to model relationships between instances. Consider the task of predicting the political preferences of users in a social network; to so…
US-X Complete: A Multi-Modal Approach to Anatomical 3D Shape Recovery
Miruna-Alexandra Gafencu, Yordanka Velikova, Nassir Navab +1
Ultrasound offers a radiation-free, cost-effective solution for real-time visualization of spinal landmarks, paraspinal soft tissues and neurovascular structures, making it valuabl…
Pathryoshka: Compressing Pathology Foundation Models via Multi-Teacher Knowledge Distillation with Nested Embeddings
Christian Grashei, Christian Brechenmacher, Rao Muhammad Umer +4
Pathology foundation models (FMs) have driven significant progress in computational pathology. However, these high-performing models can easily exceed a billion parameters and prod…
Transformer-Based Hematological Malignancy Prediction from Peripheral Blood Smears in a Real-World Cohort
Muhammed Furkan Dasdelen, Ivan Kukuljan, Peter Lienemann +6
Peripheral blood smears remain a cornerstone in the diagnosis of hematological neoplasms, offering rapid and valuable insights that inform subsequent diagnostic steps. However, sin…
MultiMAE for Brain MRIs: Robustness to Missing Inputs Using Multi-Modal Masked Autoencoder
Ayhan Can Erdur, Christian Beischl, Daniel Scholz +4
Missing input sequences are common in medical imaging data, posing a challenge for deep learning models reliant on complete input data. In this work, inspired by MultiMAE [2], we d…
DeepAf: One-Shot Spatiospectral Auto-Focus Model for Digital Pathology
Yousef Yeganeh, Maximilian Frantzen, Michael Lee +3
While Whole Slide Imaging (WSI) scanners remain the gold standard for digitizing pathology samples, their high cost limits accessibility in many healthcare settings. Other low-cost…
A Variational Framework for the Complexity of PDE Solutions
Juan Esteban Suarez Cardona, Holger Boche, Gitta Kutyniok
Partial Differential Equations (PDEs) are fundamental mathematical models for describing physical phenomena, yet most PDEs of practical interest require numerical approximations. T…
Falsification-driven reinforcement learning for maritime motion planning
Marlon Müller, Florian Finkeldei, Hanna Krasowski +2
Compliance with maritime traffic rules is essential for the safe operation of autonomous vessels, yet training reinforcement learning (RL) agents to adhere to them is challenging.…
Optimizing Prognostic Biomarker Discovery in Pancreatic Cancer Through Hybrid Ensemble Feature Selection and Multi-Omics Data
John Zobolas, Anne-Marie George, Alberto López +3
Prediction of patient survival using high-dimensional multi-omics data requires systematic feature selection methods that ensure predictive performance, sparsity, and reliability f…
BioSonix: Can Physics-Based Sonification Perceptualize Tissue Deformations From Tool Interactions?
Veronica Ruozzi, Sasan Matinfar, Laura Schütz +4
Perceptualizing tool interactions with deformable structures in surgical procedures remains challenging, as unimodal visualization techniques often fail to capture the complexity o…
On the distance between mean and geometric median in high dimensions
Richard Schwank, Mathias Drton
The geometric median, a notion of center for multivariate distributions, has gained recent attention in robust statistics and machine learning. Although conceptually distinct from…
Kernel-based Greedy Approximation of Parametric Elliptic Boundary Value Problems
Bernard Haasdonk, Gabriele Santin, Tizian Wenzel
We recently introduced a scale of kernel-based greedy schemes for approximating the solutions of elliptic boundary value problems. The procedure is based on a generalized interpola…
Area-based epigraph and hypograph indices for functional outlier detection
Belen Pulido, Alba M. Franco-Pereira, Rosa E. Lillo +1
Detecting outliers in Functional Data Analysis is challenging because curves can stray from the majority in many different ways. The Modified Epigraph Index (MEI) and Modified Hypo…
Global and Local Contrastive Learning for Joint Representations from Cardiac MRI and ECG
Alexander Selivanov, Philip Müller, Özgün Turgut +2
An electrocardiogram (ECG) is a widely used, cost-effective tool for detecting electrical abnormalities in the heart. However, it cannot directly measure functional parameters, suc…
Efficient dataset generation for machine learning perovskite alloys
Henrietta Homm, Jarno Laakso, Patrick Rinke
Lead-based perovskite solar cells have reached high efficiencies, but toxicity and lack of stability hinder their wide-scale adoption. These issues have been partially addressed th…
Large Language Models for Depression Recognition in Spoken Language Integrating Psychological Knowledge
Yupei Li, Shuaijie Shao, Manuel Milling +1
Depression is a growing concern gaining attention in both public discourse and AI research. While deep neural networks (DNNs) have been used for recognition, they still lack real-w…
UST-GNN: A Unified Spatial--Topological Graph Neural Network Framework for Urban Analytics--Demonstrated through a Case Study on Urban Health Prediction
Minwei Zhao, Sanja Scepanovic, Stephen Law +3
Understanding how social, demographic, environmental, and spatial factors jointly shape urban outcomes is essential for sustainable urban development and evidence-based policy. Tra…
On "Confirmatory" Methodological Research in Statistics and Related Fields
F. J. D. Lange, Juliane C. Wilcke, Sabine Hoffmann +2
Empirical substantive research, such as in the life or social sciences, is commonly categorized into the two modes exploratory and confirmatory, both of which are essential to scie…