activity
20242026
most citedThe Clever Hans Effect in Unsupervised Learning

33 citations · 62 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2026

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

Yanqing Luo, Julius Hense, Niklas Prenißl +4

Explanations of multiple instance learning (MIL) models are widely used for validation and discovery in digital histopathology. Existing methods primarily rely on heatmaps that hig…

cs.CV2026

Context Sensitivity Improves Human-Machine Visual Alignment

Frieda Born, Tom Neuhäuser, Lukas Muttenthaler +6

Modern machine learning models typically represent inputs as fixed points in a high-dimensional embedding space. While this approach has been proven powerful for a wide range of do…

cs.CV2026

Atlas 2 -- Foundation models for clinical deployment

Maximilian Alber, Timo Milbich, Alexandra Carpen-Amarie +24

Pathology foundation models substantially advanced the possibilities in computational pathology --- yet tradeoffs in terms of performance, robustness, and computational requirement…

cs.CV2025★ 4 cited

Atlas: A Novel Pathology Foundation Model by Mayo Clinic, Charité, and Aignostics

Maximilian Alber, Stephan Tietz, Jonas Dippel +24

Recent advances in digital pathology have demonstrated the effectiveness of foundation models across diverse applications. In this report, we present Atlas, a novel vision foundati…

cs.LG2024★ 33 cited

The Clever Hans Effect in Unsupervised Learning

Jacob Kauffmann, Jonas Dippel, Lukas Ruff +3

Unsupervised learning has become an essential building block of AI systems. The representations it produces, e.g. in foundation models, are critical to a wide variety of downstream…

cs.AI2024

AI-based Anomaly Detection for Clinical-Grade Histopathological Diagnostics

Jonas Dippel, Niklas Prenißl, Julius Hense +10

While previous studies have demonstrated the potential of AI to diagnose diseases in imaging data, clinical implementation is still lagging behind. This is partly because AI models…

eess.IV2024★ 25 cited

RudolfV: A Foundation Model by Pathologists for Pathologists

Jonas Dippel, Barbara Feulner, Tobias Winterhoff +17

Artificial intelligence has started to transform histopathology impacting clinical diagnostics and biomedical research. However, while many computational pathology approaches have…